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Speech synthesis

Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition.

Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database. Systems differ in the size of the stored speech units; a system that stores phones or diphones provides the largest output range, but may lack clarity. For specific usage domains, the storage of entire words or sentences allows for high-quality output. Alternatively, a synthesizer can incorporate a model of the vocal tract and other human voice characteristics to create a completely "synthetic" voice output.

The quality of a speech synthesizer is judged by its similarity to the human voice and by its ability to be understood clearly. An intelligible text-to-speech program allows people with visual impairments or reading disabilities to listen to written words on a home computer. Many computer operating systems have included speech synthesizers since the early 1990s.

A text-to-speech system (or "engine") is composed of two parts: a front-end and a back-end. The front-end has two major tasks. First, it converts raw text containing symbols like numbers and abbreviations into the equivalent of written-out words. This process is often called text normalization, pre-processing, or tokenization. The front-end then assigns phonetic transcriptions to each word, and divides and marks the text into prosodic units, like phrases, clauses, and sentences. The process of assigning phonetic transcriptions to words is called text-to-phoneme or grapheme-to-phoneme conversion. Phonetic transcriptions and prosody information together make up the symbolic linguistic representation that is output by the front-end. The back-end—often referred to as the synthesizer—then converts the symbolic linguistic representation into sound. In certain systems, this part includes the computation of the target prosody (pitch contour, phoneme durations), which is then imposed on the output speech.

History
Long before the invention of electronic signal processing, some people tried to build machines to emulate human speech. Some early legends of the existence of "Brazen Heads" involved Pope Silvester II (d. 1003 AD), Albertus Magnus (1198–1280), and Roger Bacon (1214–1294).

In 1779, the German-Danish scientist Christian Gottlieb Kratzenstein won the first prize in a competition announced by the Russian Imperial Academy of Sciences and Arts for models he built of the human vocal tract that could produce the five long vowel sounds (in International Phonetic Alphabet notation:, , , and ). There followed the bellows-operated "acoustic-mechanical speech machine" of Wolfgang von Kempelen of Pressburg, Hungary, described in a 1791 paper. This machine added models of the tongue and lips, enabling it to produce consonants as well as vowels. In 1837, Charles Wheatstone produced a "speaking machine" based on von Kempelen's design, and in 1846, Joseph Faber exhibited the "Euphonia". In 1923, Paget resurrected Wheatstone's design.

In the 1930s, Bell Labs developed the vocoder, which automatically analyzed speech into its fundamental tones and resonances. From his work on the vocoder, Homer Dudley developed a keyboard-operated voice-synthesizer called The Voder (Voice Demonstrator), which he exhibited at the 1939 New York World's Fair.

Dr. Franklin S. Cooper and his colleagues at Haskins Laboratories built the Pattern playback in the late 1940s and completed it in 1950. There were several different versions of this hardware device; only one currently survives. The machine converts pictures of the acoustic patterns of speech in the form of a spectrogram back into sound. Using this device, Alvin Liberman and colleagues discovered acoustic cues for the perception of phonetic segments (consonants and vowels).

Electronic devices
The first computer-based speech-synthesis systems originated in the late 1950s. Noriko Umeda et al. developed the first general English text-to-speech system in 1968, at the Electrotechnical Laboratory in Japan. In 1961, physicist John Larry Kelly, Jr and his colleague Louis Gerstman used an IBM 704 computer to synthesize speech, an event among the most prominent in the history of Bell Labs. Kelly's voice recorder synthesizer (vocoder) recreated the song "Daisy Bell", with musical accompaniment from Max Mathews. Coincidentally, Arthur C. Clarke was visiting his friend and colleague John Pierce at the Bell Labs Murray Hill facility. Clarke was so impressed by the demonstration that he used it in the climactic scene of his screenplay for his novel 2001: A Space Odyssey, where the HAL 9000 computer sings the same song as astronaut Dave Bowman puts it to sleep. Despite the success of purely electronic speech synthesis, research into mechanical speech-synthesizers continues.

Linear predictive coding (LPC), a form of speech coding, began development with the work of Fumitada Itakura of Nagoya University and Shuzo Saito of Nippon Telegraph and Telephone (NTT) in 1966. Further developments in LPC technology were made by Bishnu S. Atal and Manfred R. Schroeder at Bell Labs during the 1970s. LPC was later the basis for early speech synthesizer chips, such as the Texas Instruments LPC Speech Chips used in the Speak & Spell toys from 1978.

In 1975, Fumitada Itakura developed the line spectral pairs (LSP) method for high-compression speech coding, while at NTT. From 1975 to 1981, Itakura studied problems in speech analysis and synthesis based on the LSP method. In 1980, his team developed an LSP-based speech synthesizer chip. LSP is an important technology for speech synthesis and coding, and in the 1990s was adopted by almost all international speech coding standards as an essential component, contributing to the enhancement of digital speech communication over mobile channels and the internet.

In 1975, MUSA was released, and was one of the first Speech Synthesis systems. It consisted of a stand-alone computer hardware and a specialized software that enabled it to read Italian. A second version, released in 1978, was also able to sing Italian in an "a cappella" style. Dominant systems in the 1980s and 1990s were the DECtalk system, based largely on the work of Dennis Klatt at MIT, and the Bell Labs system; the latter was one of the first multilingual language-independent systems, making extensive use of natural language processing methods.

Handheld electronics featuring speech synthesis began emerging in the 1970s. One of the first was the Telesensory Systems Inc. (TSI) Speech+ portable calculator for the blind in 1976. Other devices had primarily educational purposes, such as the Speak & Spell toy produced by Texas Instruments in 1978. Fidelity released a speaking version of its electronic chess computer in 1979. The first video game to feature speech synthesis was the 1980 shoot 'em up arcade game, Stratovox (known in Japan as Speak & Rescue), from Sun Electronics. The first personal computer game with speech synthesis was Manbiki Shoujo (Shoplifting Girl), released in 1980 for the PET 2001, for which the game's developer, Hiroshi Suzuki, developed a "zero cross" programming technique to produce a synthesized speech waveform. Another early example, the arcade version of Berzerk, also dates from 1980. The Milton Bradley Company produced the first multi-player electronic game using voice synthesis, Milton, in the same year.

In 1976, Computalker Consultants released their CT-1 Speech Synthesizer. Designed by D. Lloyd Rice and Jim Cooper, it was an analog synthesizer built to work with microcomputers using the S-100 bus standard.

Early electronic speech-synthesizers sounded robotic and were often barely intelligible. The quality of synthesized speech has steadily improved, but output from contemporary speech synthesis systems remains clearly distinguishable from actual human speech.

Synthesized voices typically sounded male until 1990, when Ann Syrdal, at AT&T Bell Laboratories, created a female voice.

Kurzweil predicted in 2005 that as the cost-performance ratio caused speech synthesizers to become cheaper and more accessible, more people would benefit from the use of text-to-speech programs.

Synthesizer technologies
The most important qualities of a speech synthesis system are naturalness and intelligibility.  Naturalness describes how closely the output sounds like human speech, while intelligibility is the ease with which the output is understood. The ideal speech synthesizer is both natural and intelligible. Speech synthesis systems usually try to maximize both characteristics.

The two primary technologies generating synthetic speech waveforms are concatenative synthesis and formant synthesis. Each technology has strengths and weaknesses, and the intended uses of a synthesis system will typically determine which approach is used.

Concatenation synthesis
Concatenative synthesis is based on the concatenation (stringing together) of segments of recorded speech. Generally, concatenative synthesis produces the most natural-sounding synthesized speech. However, differences between natural variations in speech and the nature of the automated techniques for segmenting the waveforms sometimes result in audible glitches in the output. There are three main sub-types of concatenative synthesis.

Unit selection synthesis
Unit selection synthesis uses large databases of recorded speech. During database creation, each recorded utterance is segmented into some or all of the following: individual phones, diphones, half-phones, syllables, morphemes, words, phrases, and sentences. Typically, the division into segments is done using a specially modified speech recognizer set to a "forced alignment" mode with some manual correction afterward, using visual representations such as the waveform and spectrogram. An index of the units in the speech database is then created based on the segmentation and acoustic parameters like the fundamental frequency (pitch), duration, position in the syllable, and neighboring phones. At run time, the desired target utterance is created by determining the best chain of candidate units from the database (unit selection). This process is typically achieved using a specially weighted decision tree.

Unit selection provides the greatest naturalness, because it applies only a small amount of digital signal processing (DSP) to the recorded speech. DSP often makes recorded speech sound less natural, although some systems use a small amount of signal processing at the point of concatenation to smooth the waveform. The output from the best unit-selection systems is often indistinguishable from real human voices, especially in contexts for which the TTS system has been tuned. However, maximum naturalness typically require unit-selection speech databases to be very large, in some systems ranging into the gigabytes of recorded data, representing dozens of hours of speech. Also, unit selection algorithms have been known to select segments from a place that results in less than ideal synthesis (e.g. minor words become unclear) even when a better choice exists in the database. Recently, researchers have proposed various automated methods to detect unnatural segments in unit-selection speech synthesis systems.

Diphone synthesis
Diphone synthesis uses a minimal speech database containing all the diphones (sound-to-sound transitions) occurring in a language. The number of diphones depends on the phonotactics of the language: for example, Spanish has about 800 diphones, and German about 2500. In diphone synthesis, only one example of each diphone is contained in the speech database. At runtime, the target prosody of a sentence is superimposed on these minimal units by means of digital signal processing techniques such as linear predictive coding, PSOLA or MBROLA. or more recent techniques such as pitch modification in the source domain using discrete cosine transform. Diphone synthesis suffers from the sonic glitches of concatenative synthesis and the robotic-sounding nature of formant synthesis, and has few of the advantages of either approach other than small size. As such, its use in commercial applications is declining, although it continues to be used in research because there are a number of freely available software implementations. An early example of Diphone synthesis is a teaching robot, Leachim, that was invented by Michael J. Freeman. Leachim contained information regarding class curricular and certain biographical information about the students whom it was programmed to teach. It was tested in a fourth grade classroom in the Bronx, New York.

Domain-specific synthesis
Domain-specific synthesis concatenates prerecorded words and phrases to create complete utterances. It is used in applications where the variety of texts the system will output is limited to a particular domain, like transit schedule announcements or weather reports. The technology is very simple to implement, and has been in commercial use for a long time, in devices like talking clocks and calculators. The level of naturalness of these systems can be very high because the variety of sentence types is limited, and they closely match the prosody and intonation of the original recordings.

Because these systems are limited by the words and phrases in their databases, they are not general-purpose and can only synthesize the combinations of words and phrases with which they have been preprogrammed. The blending of words within naturally spoken language however can still cause problems unless the many variations are taken into account. For example, in non-rhotic dialects of English the "r" in words like "clear" is usually only pronounced when the following word has a vowel as its first letter (e.g. "clear out" is realized as ). Likewise in French, many final consonants become no longer silent if followed by a word that begins with a vowel, an effect called liaison. This alternation cannot be reproduced by a simple word-concatenation system, which would require additional complexity to be context-sensitive.

Formant synthesis
Formant synthesis does not use human speech samples at runtime. Instead, the synthesized speech output is created using additive synthesis and an acoustic model (physical modelling synthesis). Parameters such as fundamental frequency, voicing, and noise levels are varied over time to create a waveform of artificial speech. This method is sometimes called rules-based synthesis; however, many concatenative systems also have rules-based components. Many systems based on formant synthesis technology generate artificial, robotic-sounding speech that would never be mistaken for human speech. However, maximum naturalness is not always the goal of a speech synthesis system, and formant synthesis systems have advantages over concatenative systems. Formant-synthesized speech can be reliably intelligible, even at very high speeds, avoiding the acoustic glitches that commonly plague concatenative systems. High-speed synthesized speech is used by the visually impaired to quickly navigate computers using a screen reader. Formant synthesizers are usually smaller programs than concatenative systems because they do not have a database of speech samples. They can therefore be used in embedded systems, where memory and microprocessor power are especially limited. Because formant-based systems have complete control of all aspects of the output speech, a wide variety of prosodies and intonations can be output, conveying not just questions and statements, but a variety of emotions and tones of voice.

Examples of non-real-time but highly accurate intonation control in formant synthesis include the work done in the late 1970s for the Texas Instruments toy Speak & Spell, and in the early 1980s Sega arcade machines and in many Atari, Inc. arcade games using the TMS5220 LPC Chips. Creating proper intonation for these projects was painstaking, and the results have yet to be matched by real-time text-to-speech interfaces.

Articulatory synthesis
Articulatory synthesis consists of computational techniques for synthesizing speech based on models of the human vocal tract and the articulation processes occurring there. The first articulatory synthesizer regularly used for laboratory experiments was developed at Haskins Laboratories in the mid-1970s by Philip Rubin, Tom Baer, and Paul Mermelstein. This synthesizer, known as ASY, was based on vocal tract models developed at Bell Laboratories in the 1960s and 1970s by Paul Mermelstein, Cecil Coker, and colleagues.

Until recently, articulatory synthesis models have not been incorporated into commercial speech synthesis systems. A notable exception is the NeXT-based system originally developed and marketed by Trillium Sound Research, a spin-off company of the University of Calgary, where much of the original research was conducted. Following the demise of the various incarnations of NeXT (started by Steve Jobs in the late 1980s and merged with Apple Computer in 1997), the Trillium software was published under the GNU General Public License, with work continuing as gnuspeech. The system, first marketed in 1994, provides full articulatory-based text-to-speech conversion using a waveguide or transmission-line analog of the human oral and nasal tracts controlled by Carré's "distinctive region model".

More recent synthesizers, developed by Jorge C. Lucero and colleagues, incorporate models of vocal fold biomechanics, glottal aerodynamics and acoustic wave propagation in the bronchi, trachea, nasal and oral cavities, and thus constitute full systems of physics-based speech simulation.

HMM-based synthesis
HMM-based synthesis is a synthesis method based on hidden Markov models, also called Statistical Parametric Synthesis. In this system, the frequency spectrum (vocal tract), fundamental frequency (voice source), and duration (prosody) of speech are modeled simultaneously by HMMs. Speech waveforms are generated from HMMs themselves based on the maximum likelihood criterion.

Sinewave synthesis
Sinewave synthesis is a technique for synthesizing speech by replacing the formants (main bands of energy) with pure tone whistles.

Deep learning-based synthesis
Deep learning speech synthesis uses deep neural networks (DNN) to produce artificial speech from text (text-to-speech) or spectrum (vocoder). The deep neural networks are trained using a large amount of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.

15.ai uses a multi-speaker model—hundreds of voices are trained concurrently rather than sequentially, decreasing the required training time and enabling the model to learn and generalize shared emotional context, even for voices with no exposure to such emotional context. The deep learning model used by the application is nondeterministic: each time that speech is generated from the same string of text, the intonation of the speech will be slightly different. The application also supports manually altering the emotion of a generated line using emotional contextualizers (a term coined by this project), a sentence or phrase that conveys the emotion of the take that serves as a guide for the model during inference.

ElevenLabs is primarily known for its browser-based, AI-assisted text-to-speech software, Speech Synthesis, which can produce lifelike speech by synthesizing vocal emotion and intonation. The company states its software is built to adjust the intonation and pacing of delivery based on the context of language input used. It uses advanced algorithms to analyze the contextual aspects of text, aiming to detect emotions like anger, sadness, happiness, or alarm, which enables the system to understand the user's sentiment, resulting in a more realistic and human-like inflection. Other features include multilingual speech generation and long-form content creation with contextually-aware voices.

The DNN-based speech synthesizers are approaching the naturalness of the human voice. Examples of disadvantages of the method are low robustness when the data are not sufficient, lack of controllability and low performance in auto-regressive models.

For tonal languages, such as Chinese or Taiwanese language, there are different levels of tone sandhi required and sometimes the output of speech synthesizer may result in the mistakes of tone sandhi.

Audio deepfakes
In 2023, VICE reporter Joseph Cox published findings that he had recorded five minutes of himself talking and then used a tool developed by ElevenLabs to create voice deepfakes that defeated a bank's voice-authentication system.

Text normalization challenges
The process of normalizing text is rarely straightforward. Texts are full of heteronyms, numbers, and abbreviations that all require expansion into a phonetic representation. There are many spellings in English which are pronounced differently based on context. For example, "My latest project is to learn how to better project my voice" contains two pronunciations of "project".

Most text-to-speech (TTS) systems do not generate semantic representations of their input texts, as processes for doing so are unreliable, poorly understood, and computationally ineffective. As a result, various heuristic techniques are used to guess the proper way to disambiguate homographs, like examining neighboring words and using statistics about frequency of occurrence.

Recently TTS systems have begun to use HMMs (discussed above) to generate "parts of speech" to aid in disambiguating homographs. This technique is quite successful for many cases such as whether "read" should be pronounced as "red" implying past tense, or as "reed" implying present tense. Typical error rates when using HMMs in this fashion are usually below five percent. These techniques also work well for most European languages, although access to required training corpora is frequently difficult in these languages.

Deciding how to convert numbers is another problem that TTS systems have to address. It is a simple programming challenge to convert a number into words (at least in English), like "1325" becoming "one thousand three hundred twenty-five". However, numbers occur in many different contexts; "1325" may also be read as "one three two five", "thirteen twenty-five" or "thirteen hundred and twenty five". A TTS system can often infer how to expand a number based on surrounding words, numbers, and punctuation, and sometimes the system provides a way to specify the context if it is ambiguous. Roman numerals can also be read differently depending on context. For example, "Henry VIII" reads as "Henry the Eighth", while "Chapter VIII" reads as "Chapter Eight".

Similarly, abbreviations can be ambiguous. For example, the abbreviation "in" for "inches" must be differentiated from the word "in", and the address "12 St John St." uses the same abbreviation for both "Saint" and "Street". TTS systems with intelligent front ends can make educated guesses about ambiguous abbreviations, while others provide the same result in all cases, resulting in nonsensical (and sometimes comical) outputs, such as "Ulysses S. Grant" being rendered as "Ulysses South Grant".

Text-to-phoneme challenges
Speech synthesis systems use two basic approaches to determine the pronunciation of a word based on its spelling, a process which is often called text-to-phoneme or grapheme-to-phoneme conversion (phoneme is the term used by linguists to describe distinctive sounds in a language). The simplest approach to text-to-phoneme conversion is the dictionary-based approach, where a large dictionary containing all the words of a language and their correct pronunciations is stored by the program. Determining the correct pronunciation of each word is a matter of looking up each word in the dictionary and replacing the spelling with the pronunciation specified in the dictionary. The other approach is rule-based, in which pronunciation rules are applied to words to determine their pronunciations based on their spellings. This is similar to the "sounding out", or synthetic phonics, approach to learning reading.

Each approach has advantages and drawbacks. The dictionary-based approach is quick and accurate, but completely fails if it is given a word which is not in its dictionary. As dictionary size grows, so too does the memory space requirements of the synthesis system. On the other hand, the rule-based approach works on any input, but the complexity of the rules grows substantially as the system takes into account irregular spellings or pronunciations. (Consider that the word "of" is very common in English, yet is the only word in which the letter "f" is pronounced .) As a result, nearly all speech synthesis systems use a combination of these approaches.

Languages with a phonemic orthography have a very regular writing system, and the prediction of the pronunciation of words based on their spellings is quite successful. Speech synthesis systems for such languages often use the rule-based method extensively, resorting to dictionaries only for those few words, like foreign names and loanwords, whose pronunciations are not obvious from their spellings. On the other hand, speech synthesis systems for languages like English, which have extremely irregular spelling systems, are more likely to rely on dictionaries, and to use rule-based methods only for unusual words, or words that are not in their dictionaries.

Evaluation challenges
The consistent evaluation of speech synthesis systems may be difficult because of a lack of universally agreed objective evaluation criteria. Different organizations often use different speech data. The quality of speech synthesis systems also depends on the quality of the production technique (which may involve analogue or digital recording) and on the facilities used to replay the speech. Evaluating speech synthesis systems has therefore often been compromised by differences between production techniques and replay facilities.

Since 2005, however, some researchers have started to evaluate speech synthesis systems using a common speech dataset.

Prosodics and emotional content
A study in the journal Speech Communication by Amy Drahota and colleagues at the University of Portsmouth, UK, reported that listeners to voice recordings could determine, at better than chance levels, whether or not the speaker was smiling. It was suggested that identification of the vocal features that signal emotional content may be used to help make synthesized speech sound more natural. One of the related issues is modification of the pitch contour of the sentence, depending upon whether it is an affirmative, interrogative or exclamatory sentence. One of the techniques for pitch modification uses discrete cosine transform in the source domain (linear prediction residual). Such pitch synchronous pitch modification techniques need a priori pitch marking of the synthesis speech database using techniques such as epoch extraction using dynamic plosion index applied on the integrated linear prediction residual of the voiced regions of speech.

Dedicated hardware

 * Icophone
 * General Instrument SP0256-AL2
 * National Semiconductor DT1050 Digitalker (Mozer – Forrest Mozer)
 * Texas Instruments LPC Speech Chips

Hardware and software systems
Popular systems offering speech synthesis as a built-in capability.

Texas Instruments

In the early 1980s, TI was known as a pioneer in speech synthesis, and a highly popular plug-in speech synthesizer module was available for the TI-99/4 and 4A. Speech synthesizers were offered free with the purchase of a number of cartridges and were used by many TI-written video games (games offered with speech during this promotion included Alpiner and Parsec). The synthesizer uses a variant of linear predictive coding and has a small in-built vocabulary. The original intent was to release small cartridges that plugged directly into the synthesizer unit, which would increase the device's built-in vocabulary. However, the success of software text-to-speech in the Terminal Emulator II cartridge canceled that plan.

Mattel
The Mattel Intellivision game console offered the Intellivoice Voice Synthesis module in 1982. It included the SP0256 Narrator speech synthesizer chip on a removable cartridge. The Narrator had 2kB of Read-Only Memory (ROM), and this was utilized to store a database of generic words that could be combined to make phrases in Intellivision games. Since the Orator chip could also accept speech data from external memory, any additional words or phrases needed could be stored inside the cartridge itself. The data consisted of strings of analog-filter coefficients to modify the behavior of the chip's synthetic vocal-tract model, rather than simple digitized samples.

SAM
Also released in 1982, Software Automatic Mouth was the first commercial all-software voice synthesis program. It was later used as the basis for Macintalk. The program was available for non-Macintosh Apple computers (including the Apple II, and the Lisa), various Atari models and the Commodore 64. The Apple version preferred additional hardware that contained DACs, although it could instead use the computer's one-bit audio output (with the addition of much distortion) if the card was not present. The Atari made use of the embedded POKEY audio chip. Speech playback on the Atari normally disabled interrupt requests and shut down the ANTIC chip during vocal output. The audible output is extremely distorted speech when the screen is on. The Commodore 64 made use of the 64's embedded SID audio chip.

Atari

Arguably, the first speech system integrated into an operating system was the circa 1983 unreleased Atari 1400XL/1450XL computers. These used the Votrax SC01 chip and a finite state machine to enable World English Spelling text-to-speech synthesis.

The Atari ST computers were sold with "stspeech.tos" on floppy disk.

Apple
The first speech system integrated into an operating system that shipped in quantity was Apple Computer's MacInTalk. The software was licensed from third-party developers Joseph Katz and Mark Barton (later, SoftVoice, Inc.) and was featured during the 1984 introduction of the Macintosh computer. This January demo required 512 kilobytes of RAM memory. As a result, it could not run in the 128 kilobytes of RAM the first Mac actually shipped with. So, the demo was accomplished with a prototype 512k Mac, although those in attendance were not told of this and the synthesis demo created considerable excitement for the Macintosh. In the early 1990s Apple expanded its capabilities offering system wide text-to-speech support. With the introduction of faster PowerPC-based computers they included higher quality voice sampling. Apple also introduced speech recognition into its systems which provided a fluid command set. More recently, Apple has added sample-based voices. Starting as a curiosity, the speech system of Apple Macintosh has evolved into a fully supported program, PlainTalk, for people with vision problems. VoiceOver was for the first time featured in 2005 in Mac OS X Tiger (10.4). During 10.4 (Tiger) and first releases of 10.5 (Leopard) there was only one standard voice shipping with Mac OS X. Starting with 10.6 (Snow Leopard), the user can choose out of a wide range list of multiple voices. VoiceOver voices feature the taking of realistic-sounding breaths between sentences, as well as improved clarity at high read rates over PlainTalk. Mac OS X also includes say, a command-line based application that converts text to audible speech. The AppleScript Standard Additions includes a say verb that allows a script to use any of the installed voices and to control the pitch, speaking rate and modulation of the spoken text.

Amazon
Used in Alexa and as Software as a Service in AWS (from 2017).

AmigaOS
The second operating system to feature advanced speech synthesis capabilities was AmigaOS, introduced in 1985. The voice synthesis was licensed by Commodore International from SoftVoice, Inc., who also developed the original MacinTalk text-to-speech system. It featured a complete system of voice emulation for American English, with both male and female voices and "stress" indicator markers, made possible through the Amiga's audio chipset. The synthesis system was divided into a translator library which converted unrestricted English text into a standard set of phonetic codes and a narrator device which implemented a formant model of speech generation.. AmigaOS also featured a high-level "Speak Handler", which allowed command-line users to redirect text output to speech. Speech synthesis was occasionally used in third-party programs, particularly word processors and educational software. The synthesis software remained largely unchanged from the first AmigaOS release and Commodore eventually removed speech synthesis support from AmigaOS 2.1 onward.

Despite the American English phoneme limitation, an unofficial version with multilingual speech synthesis was developed. This made use of an enhanced version of the translator library which could translate a number of languages, given a set of rules for each language.

Microsoft Windows
Modern Windows desktop systems can use SAPI 4 and SAPI 5 components to support speech synthesis and speech recognition. SAPI 4.0 was available as an optional add-on for Windows 95 and Windows 98. Windows 2000 added Narrator, a text-to-speech utility for people who have visual impairment. Third-party programs such as JAWS for Windows, Window-Eyes, Non-visual Desktop Access, Supernova and System Access can perform various text-to-speech tasks such as reading text aloud from a specified website, email account, text document, the Windows clipboard, the user's keyboard typing, etc. Not all programs can use speech synthesis directly. Some programs can use plug-ins, extensions or add-ons to read text aloud. Third-party programs are available that can read text from the system clipboard.

Microsoft Speech Server is a server-based package for voice synthesis and recognition. It is designed for network use with web applications and call centers.

Votrax
From 1971 to 1996, Votrax produced a number of commercial speech synthesizer components. A Votrax synthesizer was included in the first generation Kurzweil Reading Machine for the Blind.

Text-to-speech systems
Text-to-speech (TTS) refers to the ability of computers to read text aloud. A TTS engine converts written text to a phonemic representation, then converts the phonemic representation to waveforms that can be output as sound. TTS engines with different languages, dialects and specialized vocabularies are available through third-party publishers.

Android
Version 1.6 of Android added support for speech synthesis (TTS).

Internet
Currently, there are a number of applications, plugins and gadgets that can read messages directly from an e-mail client and web pages from a web browser or Google Toolbar. Some specialized software can narrate RSS-feeds. On one hand, online RSS-narrators simplify information delivery by allowing users to listen to their favourite news sources and to convert them to podcasts. On the other hand, on-line RSS-readers are available on almost any personal computer connected to the Internet. Users can download generated audio files to portable devices, e.g. with a help of podcast receiver, and listen to them while walking, jogging or commuting to work.

A growing field in Internet based TTS is web-based assistive technology, e.g. 'Browsealoud' from a UK company and Readspeaker. It can deliver TTS functionality to anyone (for reasons of accessibility, convenience, entertainment or information) with access to a web browser. The non-profit project Pediaphon was created in 2006 to provide a similar web-based TTS interface to the Wikipedia.

Other work is being done in the context of the W3C through the W3C Audio Incubator Group with the involvement of The BBC and Google Inc.

Open source
Some open-source software systems are available, such as:
 * eSpeak which supports a broad range of languages.
 * Festival Speech Synthesis System which uses diphone-based synthesis, as well as more modern and better-sounding techniques.
 * gnuspeech which uses articulatory synthesis from the Free Software Foundation.

Others

 * Following the commercial failure of the hardware-based Intellivoice, gaming developers sparingly used software synthesis in later games. Earlier systems from Atari, such as the Atari 5200 (Baseball) and the Atari 2600 (Quadrun and Open Sesame), also had games utilizing software synthesis.
 * Some e-book readers, such as the Amazon Kindle, Samsung E6, PocketBook eReader Pro, enTourage eDGe, and the Bebook Neo.
 * The BBC Micro incorporated the Texas Instruments TMS5220 speech synthesis chip,
 * Some models of Texas Instruments home computers produced in 1979 and 1981 (Texas Instruments TI-99/4 and TI-99/4A) were capable of text-to-phoneme synthesis or reciting complete words and phrases (text-to-dictionary), using a very popular Speech Synthesizer peripheral. TI used a proprietary codec to embed complete spoken phrases into applications, primarily video games.
 * IBM's OS/2 Warp 4 included VoiceType, a precursor to IBM ViaVoice.
 * GPS Navigation units produced by Garmin, Magellan, TomTom and others use speech synthesis for automobile navigation.
 * Yamaha produced a music synthesizer in 1999, the Yamaha FS1R which included a Formant synthesis capability. Sequences of up to 512 individual vowel and consonant formants could be stored and replayed, allowing short vocal phrases to be synthesized.

Digital sound-alikes
At the 2018 Conference on Neural Information Processing Systems (NeurIPS) researchers from Google presented the work 'Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis', which transfers learning from speaker verification to achieve text-to-speech synthesis, that can be made to sound almost like anybody from a speech sample of only 5 seconds.

Also researchers from Baidu Research presented a voice cloning system with similar aims at the 2018 NeurIPS conference, though the result is rather unconvincing.

By 2019 the digital sound-alikes found their way to the hands of criminals as Symantec researchers know of 3 cases where digital sound-alikes technology has been used for crime.

This increases the stress on the disinformation situation coupled with the facts that In March 2020, a freeware web application called 15.ai that generates high-quality voices from an assortment of fictional characters from a variety of media sources was released. Initial characters included GLaDOS from Portal, Twilight Sparkle and Fluttershy from the show My Little Pony: Friendship Is Magic, and the Tenth Doctor from Doctor Who.
 * Human image synthesis since the early 2000s has improved beyond the point of human's inability to tell a real human imaged with a real camera from a simulation of a human imaged with a simulation of a camera.
 * 2D video forgery techniques were presented in 2016 that allow near real-time counterfeiting of facial expressions in existing 2D video.
 * In SIGGRAPH 2017 an audio driven digital look-alike of upper torso of Barack Obama was presented by researchers from University of Washington. It was driven only by a voice track as source data for the animation after the training phase to acquire lip sync and wider facial information from training material consisting of 2D videos with audio had been completed.

Speech synthesis markup languages
A number of markup languages have been established for the rendition of text as speech in an XML-compliant format. The most recent is Speech Synthesis Markup Language (SSML), which became a W3C recommendation in 2004. Older speech synthesis markup languages include Java Speech Markup Language (JSML) and SABLE. Although each of these was proposed as a standard, none of them have been widely adopted.

Speech synthesis markup languages are distinguished from dialogue markup languages. VoiceXML, for example, includes tags related to speech recognition, dialogue management and touchtone dialing, in addition to text-to-speech markup.

Applications
Speech synthesis has long been a vital assistive technology tool and its application in this area is significant and widespread. It allows environmental barriers to be removed for people with a wide range of disabilities. The longest application has been in the use of screen readers for people with visual impairment, but text-to-speech systems are now commonly used by people with dyslexia and other reading disabilities as well as by pre-literate children. They are also frequently employed to aid those with severe speech impairment usually through a dedicated voice output communication aid. Work to personalize a synthetic voice to better match a person's personality or historical voice is becoming available. A noted application, of speech synthesis, was the Kurzweil Reading Machine for the Blind which incorporated text-to-phonetics software based on work from Haskins Laboratories and a black-box synthesizer built by Votrax. Speech synthesis techniques are also used in entertainment productions such as games and animations. In 2007, Animo Limited announced the development of a software application package based on its speech synthesis software FineSpeech, explicitly geared towards customers in the entertainment industries, able to generate narration and lines of dialogue according to user specifications. The application reached maturity in 2008, when NEC Biglobe announced a web service that allows users to create phrases from the voices of characters from the Japanese anime series Code Geass: Lelouch of the Rebellion R2. 15.ai has been frequently used for content creation in various fandoms, including the My Little Pony: Friendship Is Magic fandom, the Team Fortress 2 fandom, the Portal fandom, and the SpongeBob SquarePants fandom.

Text-to-speech for disability and impaired communication aids have become widely available. Text-to-speech is also finding new applications; for example, speech synthesis combined with speech recognition allows for interaction with mobile devices via natural language processing interfaces. Some users have also created AI virtual assistants using 15.ai and external voice control software.

Text-to-speech is also used in second language acquisition. Voki, for instance, is an educational tool created by Oddcast that allows users to create their own talking avatar, using different accents. They can be emailed, embedded on websites or shared on social media.

Content creators have used voice cloning tools to recreate their voices for podcasts, narration, and comedy shows. Publishers and authors have also used such software to narrate audiobooks and newsletters. Another area of application is AI video creation with talking heads. Webapps and video editors like Elai.io or Synthesia allow users to create video content involving AI avatars, who are made to speak using text-to-speech technology.

Speech synthesis is a valuable computational aid for the analysis and assessment of speech disorders. A voice quality synthesizer, developed by Jorge C. Lucero et al. at the University of Brasília, simulates the physics of phonation and includes models of vocal frequency jitter and tremor, airflow noise and laryngeal asymmetries. The synthesizer has been used to mimic the timbre of dysphonic speakers with controlled levels of roughness, breathiness and strain.

title: Speech synthesis


text:
374

Year 374 (CCCLXXIV) was a common year starting on Wednesday (link will display the full calendar) of the Julian calendar. At the time, it was known as the Year of the Consulship of Augustus and Equitius (or, less frequently, year 1127 Ab urbe condita). The denomination 374 for this year has been used since the early medieval period, when the Anno Domini calendar era became the prevalent method in Europe for naming years.

Roman Empire

 * The Quadi cross the Danube and begin ravaging Pannonia. They avoid the fortified cities, and plunder the unprotected countryside.

Mesoamerica

 * May 4 – Spearthrower Owl ascends to the throne and becomes ruler of Teotihuacan (Mexico).

Religion

 * December 7 – The people of Milan astonish Ambrosius, governor of Aemilia-Liguria, by acclaiming him bishop. He is the second son of the former praetorian prefect of Gaul, and becomes a creative thinker whose ideas will provide the paradigm for medieval church-state relations.

Births

 * Fu Liang (or Jiyou), Chinese official and politician (d. 426)
 * Gwanggaeto the Great, Korean king of Goguryeo (d. 413)

Deaths

 * January 2 – Gregory the Elder, Christian bishop and saint (b. 276)
 * April 20 – Marcellinus of Gaul (or Marcellin), Christian bishop
 * November 17 – Pap of Armenia (or Papas), king of Armenia
 * Auxentius of Milan, Christian bishop and theologian
 * Marcellus of Ancyra, Christian bishop and saint
 * Pushyavarman, Indian ruler of Kamarupa

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: 374


text:
Nutella

Nutella is a brand of brown, sweetened hazelnut cocoa spread. Nutella is manufactured by the Italian company Ferrero and was introduced in 1964, although its first iteration dates to 1963.

History
Pietro Ferrero owned a bakery in Alba, an Italian town known for the production of hazelnuts. In 1946, he sold the initial 300 kg batch of Pasta Gianduja, derived from gianduja. Originally sold as a solid block, Ferrero started to sell a creamy version in 1951 as Supercrema gianduja.

In 1963, Ferrero's son Michele Ferrero revamped Supercrema gianduja with the intention of marketing it throughout Europe. Its composition was modified, and it was renamed "Nutella". The first jar of Nutella left the factory in Alba on April 20, 1964. The product was an instant success and remains widely popular.

In 2012, French senator Yves Daudigny proposed a tax increase on palm oil from €100 to €400 per tonne. At 20 percent, palm oil is one of Nutella's main ingredients, and the tax was dubbed "the Nutella tax" in the media.

On 14 May 2014, Poste Italiane issued a 50th anniversary Nutella commemorative stamp. The 70 Euro cent stamp was designed by Istituto Poligrafico e Zecca dello Stato and features a jar of Nutella on a golden background. Ferrero held a Nutella Day on 17 and 18 May to celebrate the anniversary.

Ingredients

The main ingredients of Nutella are sugar and palm oil (greater than 50%). It also contains 13% hazelnuts, cocoa solids, and skimmed milk. In the United States and the United Kingdom, Nutella contains soy products. Nutella is marketed as "hazelnut cream" in many countries. Under Italian law, it cannot be labeled as a "chocolate cream", as it does not meet minimum cocoa solids concentration criteria. Ferrero uses 25 percent of the global supply of hazelnuts, though not all of this is used exclusively in Nutella.

In November 2017, the company modified the recipe slightly, increasing the sugar and skimmed milk powder content. Since the colour of the product is lighter in tone, the Hamburg Consumer Protection Center estimated that the cocoa content was also reduced. Some news outlets reported that the modification of the recipe led to consumers' being "outraged" or "going nuts". Ferrero has confirmed that it has changed the recipe of its chocolate and hazelnut spread—sparking a huge backlash among fans of the brand.

The traditional Piedmont recipe, gianduja, is a mixture containing approximately 71.5% hazelnut paste and 19.5% chocolate. Nutella was developed in Piedmont, Italy, due to a lack of cocoa beans after post-war rationing reduced availability of the raw material.

Ingredients by country
Many countries have a different ingredient list for the Nutella formula.

Australia
Sugar, palm oil, hazelnuts (13%), skim milk powder (8.7%) cocoa powder (7.4%), non-fat milk solids, emulsifier (soy lecithin), flavour (vanillin).

Canada

Sugar, modified palm oil, hazelnuts, cocoa, skim milk powder, whey powder, lecithin, vanillin.

Germany
The Hamburg Consumer Protection Centre noted that the new Nutella formula introduced in November 2017 is lighter in color, estimating that it has a lower amount of cocoa content. According to 2017 reports from the Hamburg Consumer Protection Centre, the new Nutella formula has increased percentages of skim milk and sugar; the percentage of skim milk was increased from 7.5% to 8.7%, while the sugar content increased from 55.9% to 56.3%.

India
Sugar, palm oil, hazelnuts (13%), skim cow milk powder (8.7%), low fat cocoa powder (7.4%), emulsifier (Lecithin - INS 322), contains added flavour (nature identical flavouring substance - vanillin).

Italy
Sugar, palm oil, hazelnuts (13%), fat-reduced cocoa powder (7.4%), skimmed milk powder (5%), whey powder, emulsifier (lecithins) (soy), flavourant (vanillin).

United Kingdom
Sugar, palm oil, hazelnuts (13%), skimmed milk powder (8.7%), fat-reduced cocoa (7.4%), emulsifier: lecithins (soya), vanillin.

United States
Sugar, palm oil, hazelnuts, cocoa, skim milk, reduced minerals whey (milk), lecithin as emulsifier (soy), vanillin: an artificial flavor.

Nutrition
Nutella contains 10.4 percent of saturated fat and 58% of processed sugar by weight. A two-tablespoon (37-gram) serving of Nutella contains 200 calories, including 99 calories from 11 grams of fat (3.5 g of which are saturated) and 80 calories from 21 grams of sugar. The spread also contains 15 mg of sodium and 2 g of protein per serving (for reference a Canadian serving size is 1 tablespoon or 19 grams).

Production
Nutella is produced in various facilities. In the North American market, it is produced at a plant in Brantford, Ontario, Canada and more recently in San José Iturbide, Guanajuato, Mexico.

For Australia and New Zealand, Nutella has been manufactured in Lithgow, New South Wales, since the late 1970s.

Two of the four Ferrero plants in Italy produce Nutella, in Alba, Piedmont, and in Sant'Angelo dei Lombardi in Campania. In France, a production facility is located in Villers-Écalles. For Eastern Europe (including Southeast Europe, Poland, Turkey, Czech Republic and Slovakia) and South Africa, it is produced in Warsaw and Manisa. For Germany and northern Europe, Nutella is produced at the Ferrero plant in Stadtallendorf, which has been in existence since 1956. Nutella entered the Russian market and also has a production plant in Vladimir.

Ferrero also has a plant in Poços de Caldas, Brazil, which supplies the Brazilian market, with part of the production being exported overseas. It is also manufactured in Turkey and exported to countries such as India.

Global production in 2013 was about 350,000 tonnes.

Processing
Nutella is described as a chocolate and hazelnut spread, although it is mostly made of sugar and palm oil. The manufacturing process for this food item is very similar to a generic production of chocolate spread. Nutella is made from sugar, modified palm oil, hazelnuts, cocoa powder, skimmed milk powder, whey powder, soy lecithin, and vanillin.

The process of making this spread begins with the extraction of cocoa powder from the cocoa bean. These cocoa beans are harvested from cocoa trees and are left to dry for about ten days before being shipped for processing. Typically, cocoa beans contain approximately 50 percent of cocoa butter; therefore, they must be roasted to reduce the cocoa bean into a liquid form. This step is not sufficient for turning cocoa bean into a chocolate paste because it solidifies at room temperature and would not be spreadable. After the initial roast, the liquid paste is sent to presses, which are used to squeeze the butter out of the cocoa bean. The final products are round discs of chocolate made of pure compressed cocoa. The cocoa butter is transferred elsewhere so it can be used in other products.

The second process involves the hazelnuts. Once the hazelnuts have arrived at the processing plant, a quality control is issued to inspect the nuts so they are suitable for processing. A guillotine is used to chop the nuts to inspect the interior. After this process, the hazelnuts are cleaned and roasted. A second quality control is issued by a computer-controlled blast of air, which removes the bad nuts from the batch. This ensures that each jar of Nutella is uniform in its look and taste. Approximately 50 hazelnuts can be found in each jar of Nutella, as claimed by the company.

The cocoa powder is then mixed with the hazelnuts along with sugar, vanillin and skim milk in a large tank, until it becomes a paste-like spread. Modified palm oil is then added to help retain the solid phase of the Nutella at room temperature, which substitutes for the butter found in the cocoa bean. Whey powder is then added to the mix to act as a binder for the paste. Whey powder is an additive commonly used in spreads to prevent the coagulation of the product, because it stabilizes the fat emulsions. Similarly, lecithin, a form of a fatty substance found in animal and plant tissues, is added to help emulsify the paste, as it promotes homogenized mixing of the different ingredients, allowing the paste to become spreadable. It also aids the lipophilic properties of the cocoa powder, which, again, keeps the product from separating. Vanillin is added to enhance the sweetness of the chocolate. The finished product is then packaged.

Storage
The label states that Nutella does not need to be refrigerated. This is because the large quantity of sugar in the product acts as a preservative to prevent the growth of microorganisms. More specifically, the sugar acts as a preservative by binding the water in the product, which prevents the microorganisms from growing. Refrigeration causes Nutella to harden, because it contains fats from the hazelnuts. When nut fats are placed in cold temperatures, they become too hard to spread. Hazelnuts contain almost 91 percent monounsaturated fat, which are known to be liquid at room temperature and solidify at refrigerator temperatures. Room temperature allows the product to have a smooth and spreadable consistency, because the monounsaturated oils from the hazelnut are liquid in this state. In addition, the palm oil used in Nutella does not require refrigeration, because it contains high amounts of saturated fat and resists becoming rancid. The remaining ingredients in Nutella, such as cocoa, skimmed milk powder, soy lecithin, and vanillin, also do not require refrigeration.

Class action lawsuit
In the United States, Ferrero was sued in a class action for false advertising leading to consumer inferences that Nutella has nutritional and health benefits (from advertising claims that Nutella was "part of a nutritious breakfast").

In April 2012, Ferrero agreed to pay a $3 million settlement (up to $4 per jar for up to five jars per customer). The settlement also required Ferrero to make changes to Nutella's labeling and marketing, including television commercials and their website.

title: Nutella


text:
Sophie B. Hawkins

Sophie Ballantine Hawkins (born November 1, 1964) is an American singer-songwriter, musician and painter. Born in New York City, she attended the Manhattan School of Music for a year as a percussionist before leaving to pursue a music career. She achieved critical and commercial success with her first two albums, producing a string of single hits including "Damn I Wish I Was Your Lover", "Right Beside You", and "As I Lay Me Down". A dispute with her record label Sony Music over her third album, Timbre, led her to establish her own independent label, Trumpet Swan Productions, which has published her subsequent recordings.

Hawkins is a long-time supporter of animal rights and environmental causes. She is also a social and political activist, supporting events promoting women in music and LGBT rights.

Career
Hawkins's debut album, Tongues and Tails, was released in 1992. It achieved both worldwide commercial success and critical acclaim, earning her a Grammy Award nomination for Best New Artist in 1993. The single "Damn I Wish I Was Your Lover" went to number 5 on the Billboard Hot 100 singles chart in the US and was also a Top 20 hit in the UK, peaking at number 14. Hawkins was asked to perform Bob Dylan's "I Want You", which she had covered on Tongues and Tails, for the 1992 Madison Square Garden concert honoring Dylan's 30th anniversary as a musician; this was later released as The 30th Anniversary Concert Celebration, but her performance was omitted.

Whaler, her second album, was released in 1994. Produced by Stephen Lipson, it also contained a US top 10 hit, "As I Lay Me Down", and was certified gold. Three singles from the album made the UK Top 40, including "Right Beside You", which peaked at number 13. The same year, Hawkins posed nude for Interview. As she explained to Ed Rampell in an interview for Q magazine, she met the photographer, Bruce Weber, and was asked if she would do a photoshoot with him. While she had provided her own clothes, Weber deliberately had her wear an unflattering dress as part of his plan to convince Hawkins to disrobe during the shoot.

A 1998 documentary by Gigi Gaston, The Cream Will Rise, followed Hawkins during one of her tours and captured her struggle to deal with past troubles with her family, including her mother and brother. Music by Hawkins was included throughout the film.

Also in 1998, Hawkins's record company, Sony Music, delayed the release of her third album. Its executives were unhappy with the finished product and wanted Hawkins to rework some of the material. In particular, they insisted that Hawkins remove a banjo track from one of the songs. Unwilling to compromise her artistic integrity, Hawkins refused to accommodate them. After a lengthy battle between Hawkins and the company, the album, Timbre, was eventually released in 1999, though Sony declined to promote it. Hawkins subsequently left the label and founded her own label, Trumpet Swan Productions. In 2001, Timbre was re-released on Hawkins's label, now as a two-disc set that contained new songs, demos, remixes, and videos. Her first independently recorded and released album, Wilderness, was released in 2004.

In 2012, Hawkins starred as Janis Joplin in the play, Room 105, which was written and directed by her longtime girlfriend and manager, Gigi Gaston. After another long hiatus, she released her fifth album of all-new material in 2012, titled The Crossing.

On April 4, 2013, Hawkins appeared as herself on the TV series Community in the episode "Herstory of Dance", performing "Damn I Wish I Was Your Lover" and "As I Lay Me Down" during the community college's "Sophie B. Hawkins Dance," so named because Britta confused her with Susan B. Anthony in an attempt to compete with a Sadie Hawkins Dance.

In 2019, Hawkins completed a sold-out tour around the U.S.; the same year she also appeared on the German TV show Night Grooves, singing several songs, discussing her past, and showing off her drumming talent.

Personal life
Hawkins has two children, Dashiell (b. 2008) and Esther Ballantine (b. 2015). Esther had been conceived 20 years earlier and frozen as an embryo.

In an interview with Rock Cellar Magazine in 2012, Hawkins said that she identified as omnisexual. Although there were rumors she had dated Martina Navratilova and Jodie Foster, she denied those, saying, "I've never met any of the women I'm supposed to have had affairs with."

In 2012, Hawkins and Gigi Gaston shared a house in Venice, California.

Politics
In August 2007, Hawkins headlined the first Los Angeles Women's Music Festival in support of its dual agenda of supporting animal rescue groups and promoting and supporting female musicians. Hawkins is a long-time supporter of animal rights.

In February 2008, Hawkins re-recorded her song "Damn I Wish I Was Your Lover" as "Damn, We Wish You Were President" in support of presidential candidate Hillary Clinton. Hawkins also wrote in her blog, "Hillary Clinton's achievements come from her heart. She has initiated so much positive change for families, children, victims of crime and the environment in her struggle for the forward movement of America and the working people of this nation."

In May 2010, Hawkins began supporting Waterkeeper Alliance, an organization of on-the-water advocates who patrol and protect more than 100,000 miles of rivers, streams and coastlines in North and South America, Europe, Australia, Asia and Africa. She donated all of the proceeds of her single "The Land, the Sea, and the Sky" to the organization.

In February 2011, Hawkins performed at the Big Gay Party event staged by GOProud, an organization of gay conservatives, as part of the year's Conservative Political Action Conference festivities. In an after-show interview in the reason.tv documentary "Liberal in Bed, Conservative in the Head: Sophie B. Hawkins", Hawkins gave her views on issues such as gun ownership, the free market, limited government and identity politics.

In 2017, Hawkins lent her voice in support of LGBTQ youth suicide prevention organization The Trevor Project's 20th Anniversary celebration video campaign.

Awards and nominations
{| class=wikitable ! Year !! Awards !! Work !! Category !! Result !! Ref.
 * rowspan=2|1993
 * Grammy Awards
 * rowspan=3|Herself
 * Best New Artist
 * Nominated
 * Q Awards
 * Best New Act
 * Nominated
 * rowspan=2|1995
 * RSH Gold Awards
 * Kraftrille des Jahres
 * Won
 * Cash Box Year-End Awards
 * rowspan=3|"As I Lay Me Down"
 * Top Pop Single
 * Nominated
 * rowspan=2|1996
 * ASCAP Pop Music Awards
 * Most Performed Song
 * Won
 * APRA Music Awards
 * Most Performed Foreign Work
 * Nominated
 * rowspan=2|1996
 * ASCAP Pop Music Awards
 * Most Performed Song
 * Won
 * APRA Music Awards
 * Most Performed Foreign Work
 * Nominated
 * APRA Music Awards
 * Most Performed Foreign Work
 * Nominated
 * Nominated

Discography

 * Tongues and Tails (1992)
 * Whaler (1994)
 * Timbre (1999)
 * Wilderness (2004)
 * The Crossing (2012)
 * Free Myself (2023)

Filmography

 * The Cream Will Rise (1998) dir. Gigi Gaston
 * Beyond the City Limits (Rip It Off) (2001) dir. Gigi Gaston
 * Community episode "Herstory of Dance" (2013)

title: Sophie B. Hawkins


text:
Video CD

Video CD (abbreviated as VCD, and also known as Compact Disc Digital Video) is a home video format and the first format for distributing films on standard 120 mm optical discs. The format was widely adopted in Southeast Asia, South Asia, East Asia, Central Asia and West Asia, superseding the VHS and Betamax systems in the regions until DVD-Video finally became affordable in the first decade of the 21st century.

The format is a standard digital data format for storing video on a compact disc. VCDs are playable in dedicated VCD players and widely playable in most DVD players, personal computers and some video game consoles. However, they are less playable in most Blu-ray Disc players, vehicle audio with DVD/Blu-ray support and video game consoles such as the Sony PlayStation and Xbox due to lack of backward compatibility for the older MPEG-1 format, inability to read MPEG-1 in .dat files alongside MPEG-1 in standard MPEG-1, AVI, and Matroska files, or inability to read CD-ROM XA discs. Some Laserdisc players that were released in the late 90s support VCD as well as the Sony PS1 model SCPH-5903 marketed in Southeast Asia.

The Video CD standard was created in 1993 by Sony, Philips, Matsushita and JVC; it is referred to as the White Book standard. The MPEG-1 format was also released that same year.

Brief history
LaserDisc was first available on the market, in Atlanta, Georgia, on December 15, 1978. This 30 cm disc could hold an hour of analog audio and video (digital audio was added a few years later) on each side. The LaserDisc provided picture quality nearly double that of VHS tape and analog audio quality far superior to cheap mono VHS recorders (although the difference to the more expensive VHS HiFi stereo recorders was minuscule).

Philips later teamed up with Sony to develop a new type of disc, the compact disc or CD. Introduced in 1982 in Japan (1983 in the U.S. and Europe), the CD is about 120 mm in diameter, and is single-sided. The format was initially designed to store digitized sound and proved to be a success in the music industry.

A few years later, Philips decided to give CDs the ability to produce video, utilizing the same technology as its LaserDisc counterpart. This led to the creation of CD Video (CD-V) in 1987. However, the disc's small size significantly impeded the ability to store analog video; thus only 5 minutes of picture information could fit on the disc's surface (despite the fact that the audio was digital). Therefore, CD-V distribution was limited to featuring music videos, and it was soon discontinued by 1991.

By the early 1990s engineers were able to digitize and compress video signals, greatly improving storage efficiency. Because this new format could hold 74/80 minutes of audio and video on a 650/700MB disc, releasing movies on compact discs finally became a reality. Extra capacity was obtained by sacrificing the error correction (it was believed that minor errors in the datastream would go unnoticed by the viewer). This format was named Video CD or VCD.

VCD enjoyed a brief period of success, with a few major feature films being released in the format (usually as a 2 disc set). However the introduction of the CD-R disc and associated recorders stopped the release of feature films in their tracks because the VCD format had no means of preventing unauthorized (and perfect) copies from being made. However, VCDs are still being released in several countries in Asia, but now with copy-protection.

The development of more sophisticated, higher capacity optical disc formats yielded the DVD format, released only a few years later with a copy protection mechanism. DVD players use lasers that are of shorter wavelength than those used on CDs, allowing the recorded pits to be smaller, so that more information can be stored. The DVD was so successful that it eventually pushed VHS out of the video market once suitable recorders became widely available. Nevertheless, VCDs made considerable inroads into developing nations, where they are still in use today due to their cheaper manufacturing and retail costs.

Structure
Video CDs comply with the CD-i Bridge format, and are authored using tracks in CD-ROM XA mode. The first track of a VCD is in CD-ROM XA Mode 2 Form 1, and stores metadata and menu information inside an ISO 9660 filesystem. This track may also contain other non-essential files, and is shown by operating systems when loading the disc. This track can be absent from a VCD, which would still work but would not allow it to be properly displayed in computers.

The rest of the tracks are usually in CD-ROM XA Mode 2 Form 2 and contain video and audio multiplexed in an MPEG program stream (MPEG-PS) container, but CD audio tracks are also allowed. Using Mode 2 Form 2 allows roughly 800 megabytes of VCD data to be stored on one 80 minute CD (versus 700 megabytes when using CD-ROM Mode 1). This is achieved by sacrificing the error correction redundancy present in Mode 1. It was considered that small errors in the video and audio stream pass largely unnoticed. This, combined with the net bitrate of VCD video and audio, means that almost exactly 80 minutes of VCD content can be stored on an 80-minute CD, 74 minutes of VCD content on a 74-minute CD, and so on. This was done in part to ensure compatibility with existing CD drive technology, specifically the earliest "1x" speed CD drives.

Video
Video specifications
 * Compression: MPEG-1
 * Aspect Ratio: 4:3
 * Resolution:
 * analog NTSC compatible: 352×240 (240p)
 * analog PAL/SECAM compatible: 352×288 (288p)
 * Framerate:
 * analog NTSC compatible : 29.97 or 23.976 frames per second
 * analog PAL/SECAM compatible : 25 frames per second
 * Bitrate: 1,150 kilobits per second (constant bitrate)

Although many DVD video players support playback of VCDs, VCD video is only compatible with the DVD-Video standard if encoded at 29.97 frames per second or 25 frames per second.

The 352×240 and 352×288 (or SIF) resolutions, when compared to the CCIR 601 specifications (defining the appropriate parameters for digital encoding of NTSC and PAL/SECAM TV signals), are reduced by half in all aspects: height, width, frame-rate, and chrominance.

Audio
Audio specifications
 * Compression: MPEG-1 Audio Layer II
 * Sample Frequency: 44,100 hertz (44.1 kHz)
 * Output: Dual channel, stereo, or Dolby Surround
 * Bitrate: 224 kilobits per second (constant bitrate)

As with most CD-based formats, VCD audio is incompatible with the DVD-Video standard due to a difference in sampling frequency; DVDs require 48 kHz, whereas VCDs use 44.1 kHz.

Advantages of compression
By compressing both the video and audio streams, a VCD is able to hold 74 minutes of picture and sound information, the same duration as a standard 74 minute audio CD. The MPEG-1 compression used records mostly the differences between successive video frames, rather than write out each frame individually. Similarly, the audio frequency range is limited to those sounds most clearly heard by the human ear.

Other features
The VCD standard also features the option of DVD-quality still images/slide shows with audio, at resolutions of 704×480 (480i, analog NTSC compatible) or 704×576 (576i, analog PAL/SECAM compatible). Version 2.0 also adds the playback control (PBC), featuring a simple menu like DVD-Video.

CD-i Digital Video
Shortly before the advent of White Book VCD, Philips started releasing movies in the Green Book CD-i format, calling the subformat CD-i Digital Video (CD-i DV). While these used a similar format (MPEG-1), due to minor differences between the standards these discs are not compatible with VCD players. Philips' CD-i players with the Full Motion Video MPEG-1 decoder cartridge would play both formats. Approximately 30 CD-i DV titles were released before the company switched to the current VCD format for publishing movies in 1994.

XVCD
XVCD (eXtended Video CD) is the name generally given to any format that stores MPEG-1 video on a compact disc in CD-ROM XA Mode 2 Form 2, but does not strictly follow the VCD standard in terms of the encoding of the video or audio.

A normal VCD is encoded to MPEG-1 at a constant bit rate (CBR), so all scenes are required to use exactly the same data rate, regardless of complexity. However, video on an XVCD is typically encoded at a variable bit rate (VBR), so complex scenes can use a much higher data rate for a short time, while simpler scenes will use lower data rates. Some XVCDs use lower bitrates in order to fit longer videos onto the disc, while others use higher bitrates to improve quality. MPEG-2 may be used instead of MPEG-1.

To further reduce the data rate without significantly reducing quality, the size of the GOP can be increased, a different MPEG-1 quantization matrix can be used, the maximum data rate can be exceeded, and the bit rate of the MP2 audio can be reduced or even be swapped out completely for MP3 audio. These changes can be advantageous for those who want to either maximize video quality, or use fewer discs.

KVCD
KVCD (K Video Compression Dynamics) is an XVCD variant that requires the use of a proprietary quantization matrix, available for non-commercial use. In addition to standard VCD resolutions, KVCD allows for non-standard resolutions like 528×480/576, though hardware support for KVCDs authored with these resolutions is limited.

DVCD
DVCD or Double VCD is a method to accommodate longer videos on a CD. A non-standard CD is overburned to include up to 100 minutes of video. However, some CD-ROM drives and players have problems reading these CDs, mostly because the groove spacing is outside specifications and the player's laser servo is unable to track it.

DVI
DVI (Digital Video Interactive) is a compression technique that stored 72 minutes of video on a CD-ROM. In 1998, Intel acquired the technology from RCA's Sarnoff Research Labs. DVI never caught on.

SVCD
Super Video CD is a format intended to be the successor of VCD, offering better quality of image and sound. The format uses MPEG-2 video at 480x480 or 480x576 and supports multiple bitrate and channel options for encoding audio.

In North America
Video CDs were unable to gain acceptance as a mainstream format in North America, chiefly because the established VHS format was less expensive, offered comparable video quality, and could be recorded over. The advent of recordable CDs, inexpensive recorders, and compatible DVD players spurred VCD acceptance in the US in the late 1990s and early 2000s. However, DVD burners and DVD-Video recorders were available by that time, and equipment and media costs for making DVD-Video fell rapidly. DVD-Video, with its longer run time and much higher quality, quickly overshadowed VCD in areas that could afford it. In addition many early DVD players could not read recordable (CD-R) media, and this limited the compatibility of home-made VCDs.

In Asia
The VCD format was very popular throughout Asia (except Japan and South Korea) in the late 1990s through the 2000s, with 8 million VCD players sold in China in 1997 alone, and more than half of all Chinese households owning at least one VCD player by 2005. However, popularity has declined over the years, as the number of Hong Kong factories that produced VCDs dropped from 98 in 1999 to 26 in 2012.

This popularity was due, in part, to most households not already owning VCRs when VCDs were introduced, the low price of the players, their tolerance of high humidity (a notable problem for VCRs), easy storage and maintenance, and the lower-cost media. Western sources have cited unauthorized content as a principal incentive for VCD player ownership.

VCDs are often produced and sold in Asian countries and regions, such as China (including Hong Kong), Taiwan, Singapore, Malaysia, Thailand, Cambodia, Laos, Brunei, Myanmar, Indonesia, Philippines, Vietnam, Bangladesh, India, Turkey, Pakistan and Afghanistan. In many Asian countries, major Hollywood studios (and Asian home video distributors) have licensed companies to officially produce and distribute the VCDs, such as Intercontinental Video Ltd. of Hong Kong, Sunny Video in Malaysia, Vision Interprima Pictures in Indonesia, CVD International and Pacific Marketing and Entertainment Group in Thailand, Excel Home Entertainment in India, Berjaya-HVN and InnoForm Media in both Malaysia and Singapore, Scorpio East Entertainment in Singapore, as well as Viva Video, Magnavision Home Video, and C-Interactive Digital Entertainment in the Philippines. Legal Video CDs can often be found in established video stores and major book outlets in most Asian countries. They are typically packaged in jewel cases like commercial CDs, though higher-profile films may be released in keep cases, differentiated by the VCD logo.

In Asia, the use of VCDs as carriers for karaoke music is very common. One channel would feature a mono track with music and singing, another channel a pure instrumental version for karaoke singing. Prior to this, karaoke music was carried on LaserDiscs.

Worldwide trends
VCD's growth had slowed in areas that can afford DVD-Video, which offered most of the same advantages, as well as better picture quality (higher resolution with fewer digital compression artifacts) due to its larger storage capacity. However, VCD had simultaneously seen significant growth in emerging economies like India, Indonesia, South America, and Africa as a low-cost alternative to DVD. As of 2004, the worldwide popularity of VCD was increasing.

Compared with VHS
Overall picture quality is intended to be comparable to VHS video. Poorly compressed VCD video can sometimes be of lower quality than VHS video, for example exhibiting VCD block artifacts (rather than the analog noise seen in VHS sources), but does not deteriorate further with each use. Producing video CDs involves stripping out high- and low-frequency sounds from the video, resulting in lower audio quality than VHS. While both formats need fast-forwarding to find certain scenes, rewinding to the beginning upon reaching the end is not required in VCD. The resolution is just half below that of common VHS resolution.

Video CDs did not come with closed captioning (on-screen text to aid viewers with hearing problems). When watching a film that exceeds 74 minutes (nearly 1¼ hours), the maximum video capacity of one disc, a viewer had to change the disc upon reaching halfway (unless the discs were played on a VCD changer that could hold multiple discs and play them automatically in succession), whereas a single VHS tape could hold 3.5 hours of continuous video.

Compared with DVD
When playing a DVD, the viewer is taken to a main menu which gives them options (watch the feature film, view "deleted scenes", play some special applications, etc.). VCDs are usually straightforward; playing them often goes directly to the video with extras (mostly trailers and commercials) taking place before or after it, like on a VHS cassette.

Subtitles are found on many Asian VCDs but cannot be removed, unlike on DVDs. The subtitles are embedded on the video during the encoding process ("hardsubbed"). It is not uncommon to find a VCD with subtitles for two languages.

Though the VCD technology can support it, most films carried on VCDs do not contain chapters, requiring the viewer to fast-forward to resume the program after playback has been stopped. This is mostly because VCD technology is able to start playback at a chapter point but there is nothing to signal to the player that the chapter has changed during a program. This can be confusing for the user as the player will indicate that it is still playing chapter 1 when it has played through to chapter 2 or later. Pressing the Next button would cause playback from the beginning of chapter 2. However, preview material is sometimes stored in a separate chapter, followed by a single chapter for the film.

VCDs are often bilingual. Because they feature stereo audio, disc players have an option to play only the left or right audio channel. On some films, they feature English on the left audio channel and Cantonese on the right; more commonly Hong Kong VCDs will feature Mandarin on one channel and Cantonese on the other. This is similar to selecting a language track on a DVD, except it is limited to 2 languages, due to there being only two audio channels (left and right). The audio track effectively becomes monaural.

VCD's most noticeable disadvantage compared to DVD is image quality, due both to the more aggressive compression necessary to fit video into such a small capacity as well as to the compression method used. Additionally, VCD movie surround sound capability is limited to Dolby Surround matrixed within the stereo tracks, while DVDs are capable of six channels of discrete surround sound via Dolby Digital AC-3.

Hardware and software support
Early devices supporting Video CD playback include the Philips CD-i systems and the Amiga CD-32 (albeit via an optional decoder card). Disc playback is also available both natively and as an option on some CD- and DVD-based video game consoles, including the original PlayStation (only on the SCPH-5903 model).

Early software supporting Video CD playback include XingMPEG. Early PC hardware supporting Video CD playback include proprietary VCD decoder card. Later, because the introduction of Pentium II processor which supports MMX extension, and later graphics cards had included video decoding function, the use of VCD decoder card declined.

VLC is a free, open-source media player software which supports VCD on Windows, MacOS, Linux and BSD.

Windows Media Player prior to version 9 does not support playing VCD directly. Windows Vista added native support of VCD along with DVD-Video and can launch the preferred application upon insertion. The disc format is also supported natively by Media Player Classic, VLC Media Player and MPlayer.

QuickTime Player also does not support playing VCD directly, though it can play the .DAT files (stored under \MPEGAV for video and audio data) reliably, and plugins were available.

Direct access playback support is available within Windows XP MCE, Windows Vista and newer (including Windows 10), classic Mac OS, BSD, macOS, and Linux among others, either directly or with updates and compatible software.

Most DVD players are compatible with VCDs, and VCD-only players are available throughout Asia, and online through many shopping sites. Some older Blu-ray and HD-DVD players also retained support, as do CBHD players as well. However, most Blu-ray players, most vehicle audio with DVD/Blu-ray support, Xbox family, and the Sony PlayStation (2/3/4/5) cannot play VCDs; this is because while they have backwards playback compatibility with the DVD standard, these player can not read VCD data because the player software does not have support for MPEG-1 video and audio, the player software lacks ability to read MPEG-1 stream in DAT files alongside MPEG-1 stream in standard MPEG, AVI, and Matroska files, or the player lacks ability to read CD-ROM XA discs.

title: Video CD