Ildar Farkhatdinov
email: i.farkhatdinov@qmul.ac.uk

Hannah Michalska

Alain Berthoz

Vincent Hayward

Review of Anthropomorphic Head Stabilisation and Verticality Estimation in Robots

In many walking, running, flying, and swimming animals, including mammals, reptiles, and birds, the vestibular system plays a central role for verticality estimation and is often associated with a head stabilisation (in rotation) behaviour. Head stabilisation, in turn, subserves gaze stabilisation, postural control, visual-vestibular information fusion and spatial awareness via the active establishment of a quasi-inertial frame of reference. Head stabilisation helps animals to cope with the computational consequences of angular movements that complicate the reliable estimation of the vertical direction. We suggest that this strategy could also benefit free-moving robotic systems, such as locomoting humanoid robots, which are typically equipped with inertial measurements units. Free-moving robotic systems could gain the full benefits of inertial measurements if the measurement units are placed on independently orientable platforms, such as a human-like heads. We illustrate these benefits by analysing recent humanoid robots design and control approaches.

Introduction

Spatial awareness is crucial for free-moving robots. For instance, legged humanoid robots must be aware of their body motion and orientation with respect to gravity in order to maintain stable posture and gait. Recent technological developments in sensing and control for robotic systems contributed to the appearance of new humanoid robots with human-like (anthropomorphic) behaviours. However, the performance of robots is still lagging far behind the abilities of biological systems. For example, it is clear that that a powerful and adaptive sensorimotor control system enables humans, for example, to balance on fallen trunks or run on sandy beaches, not mentioning the locomotion prowesses of felines, of mountain goats, and so on.

The purpose of this chapter is to examine the phenomenon of head stabilisation displayed by biological and robotic systems and the importance of such behavior in motion sensing and body balancing. Head stabilisation has been extensively studied by neuroscientists and recently several robotic systems have adopted this human-like control to improve inertial sensing, gaze and postural control, and interaction qualities of the robots. Functions of the vestibular system and its primary roles are first reviewed in Section 2. Head stabilisation in humans is next discussed in Section 3, which is then followed by the overview of inertial sensing and head stabilisation in robotics systems in Sections 5 and 6.

2 Sensing body movements in animals and robots

Sense of motion

Humans and animals have a complex multisensory system which provides the central neural system (CNS) with information about the external world. For us, like for other living creatures, it is important to understand the spatial orientation and localization of our bodies with respect to the objects of the external world. This can be accomplished by the help of diverse sensory systems: vision, audition, tactile, proprioception and vestibular. Change of visual flow in the retina would indicate that the position of the body changed with respect to an observed environment. Change of difference in acoustic flow in the ear would indicate that the body moves with respect to a sound source. Likewise, tactile and proprioceptive inputs would signal position change of the body if the latter interacts with an environment. However, independent sensory information of one modality only may not be sufficient for correct motion perception. For instance, change of visual flow can be caused by movements of eyes, sound source movement may be estimated wrongly if the head rotates, etc. Then, the problem is solved by multisensory integration [START_REF] Ernst | Merging the senses into a robust percept[END_REF]. The CNS can efficiently process multisensory information and provide the brain with a proper motion sensation. Visual, audition, tactile and proprioception sensory inputs, excluding vestibular, can be easily put out of action while vestibular inputs will always be there. Even in case of zero gravity vestibular organs will respond to linear accelerations and angular velocities of the body motion. It is thus reasonable to claim that the vestibular system plays a key role in perceiving self-motion. The principles which govern vestibular organs and their roles for postural control will be described next.

Vestibular system

The vestibular system detects motion of the head in space and generates reflexes that are crucial for survival, such as stabilising gaze and maintaining head and body posture. In addition, the vestibular system provides its owner with a subjective sense of movement and orientation in space. The vestibular sensory organs are located in close proximity to the cochlea, as shown in Figure 1A. The vestibular system consists of two types of organs: the two otolith organs and the three semicircular canals. Two types of otolith organs (the saccule and utricle) sense linear acceleration which includes gravitational and translational forces. Semicircular canals sense angular velocities in three planes. Receptor signals are sent through the vestibular nerve fibres to the neural structures that are responsible for eye movements, posture and balance control. As a result, the vestibular organs constitute our sixth sense -the sense of motion which allows us to perceive and control bodily movements [START_REF] Berthoz | The Brain's Sense of Movement[END_REF]. Vestibular processing is highly multimodal, for instance, visual/vestibular and proprioceptive/vestibular sensory inputs are dominant for gaze and postural control, but at the same time vestibular system itself plays an important role in everyday activities and contributes to a various range of functions [START_REF] Angelaki | Vestibular system: the many facets of a multimodal sense[END_REF][START_REF] Cullen | The vestibular system: multimodal integration and encoding of self-motion for motor control[END_REF]. Each inner ear has three semicircular canals arrayed approximately at right angles to each other. The real geometry has evolved during evolution depending upon the need of each species [START_REF] David | Assessing morphology and function of the semicircular duct system: introducing new in-situ visualization and software toolbox[END_REF]. Semicircular canals are sensitive to angular accelerations [121]. Each canal is comprised of a circular path of fluid continuity, interrupted at the ampulla by a watertight, elastic membrane called the cupula [START_REF] Angelaki | Vestibular system: the many facets of a multimodal sense[END_REF]. Fig. 1B shows a schematic view of one semicircular canal. Each canal is filled with a fluid called endolymph. When the head rotates in the plane of a semicircular canal, inertial forces causes the endolymph in the canal to lag behind the motion of the head [START_REF] Carey | Principles of applied vestibular physiology[END_REF]. The motion of the endolymph applies pressure to the membrane of the cupula and its deflection causes shearing stress in the hair cells [START_REF] Carey | Principles of applied vestibular physiology[END_REF]. The corresponding electrical signals are generated and transmitted through neurons in a way similar to the way it is done in the otoliths. Although the semicircular canals respond to angular acceleration, the neural output from the sensory cells represents the velocity of rotation. This suggests that the input signal is integrated due to the mechanics of the canals, mainly because of the increase in viscous properties of the fluid in a tight canal [START_REF] Curthoys | Semicircular duct and ampulla dimensions in cat, guinea pig and man[END_REF][START_REF] Igarashi | Volumetric and dimensional measurements of vestibular structures in the squirrel monkey[END_REF]. The vestibular system transmits the components of the angular velocity of the head to the CNS which forms a three-dimensional angular velocity vector describing the body motion. More advanced experimental studies with human subjects supported the torsion-pendulum representation of the canal dynamics [START_REF] Hulk | The turning test with small regulable stimuli[END_REF]68,107]. In [139], it was suggested to model semicircular canals with the heavily-damped second order system which behaved as an angular-velocity meter.

The otolith organ comprised utricle and saccule, both sensitive to linear acceleration of the head in linear motion and static tilt in the vertical planes. The utricle and the saccule are arranged to respond to the motion in three dimensions. When the head is upright, the saccule is vertical and it measures linear accelerations in the sagittal plane, specifically movements up and down. The utricle is horizontally oriented and measures accelerations in interaural transverse (horizontal) plane (anterio-posterior and medio-lateral accelerations) [START_REF] Hain | Anatomy and physiology of vestibular system[END_REF]. Both, the utricle and the saccule, contain sheets of hair cells a sensory epithelium (macula). An otolithic membrane (otoconia) composed of calcium carbonate crystals sits atop of hair cells. Fig. 1C shows the simplified view of otolithic hair cells during an accelerated motion to the right. In response to linear acceleration, the crystals are left behind due to their inertia. Linear acceleration of the head causes otoconia's motion which in turn causes shear forces acting on the hair cells. In addition during head tilt they can measure the changes of head angle with respect to the gravity vector. Complex molecular level mechanic-electrochemical mechanism of interaction between hair cells results in the generation of electrical signals which are sent to the neural structures for further processing [START_REF] Carey | Principles of applied vestibular physiology[END_REF]. The displacement of the large saccular otolith of a ruff was measured in [START_REF] Vries | The mechanics of the labyrinth otoliths[END_REF] and the dynamic identification suggested that the mechanics of the otolith could be described by a critically damped second-order system with a resonant frequency of 50 Hz. A recent model of the geometry of the utriculus and sacculus has suggested that the curved shape of the striola (which contains the dynamic sensory cells) are in fact the projection of a curved virtual striola giving the ensemble of the two sensors the capacity to measure directly the 3D acceleration vector of the movements for the head in space [START_REF] Dimiccoli | A functional explanation of otolith geometry[END_REF].

Sensory data integration and processing

Sensory outputs from otoliths and semicircular canals are processed in neural systems on different levels. Some information is processed in low-level neural networks, while some are directed to CNS where integration with other sensory modalities may occur.

L. R. Young with his group proposed an optimal estimator model in [START_REF] Borah | Optimal estimator model for human spatial orientation[END_REF]. A concept of the internal model was introduced which comprised the dynamic model information about the sensory organs and head-neck system. This internal model was considered to be known for the CNS. L. R. Young used an optimal estimator (Kalman filter) to estimate the human's orientation based on the outputs from visual, vestibular, proprioceptive and tactile sensory systems. Assumptions about sensor dynamics and noise statistic from internal model were used to correct the estimated states which represented spatial orientation. Estimated states, called as perceptions, contained angular orientation of the head, its angular velocity, inertial translation and inertial velocity.

In similarity with [START_REF] Borah | Optimal estimator model for human spatial orientation[END_REF], an internal model based approach was proposed by D.M. Merfeld and colleagues in [START_REF] Merfeld | Humans use internal models to estimate gravity and linear acceleration[END_REF]. Their sensory integration model was based on simulating the neural processing of gravito-inertial cues. In [151, 101] experiments were performed to analyse the vestibular-ocular response during tilt and rotation of the head and the body. The presented experimental findings were consistent with the hypothesis that the nervous system resolves the ambiguous measurements of gravitoinertial forces into neural estimates of gravity and linear acceleration. A human model for this vestibular signals processing was presented in [100]. A linear system was used to model the semicircular canals' dynamics, and a simple gain (identity matrix) was used to model the otoliths. It was suggested that the CNS is able to perform the operation of gravitational vector transformation (rotation) from the world frame to the head's frame.

More recently, J. Laurens and J. Droulez built a Bayesian processing model of self-motion perception in [START_REF] Laurens | Bayesian processing of vestibular information[END_REF]. It was proposed that the brain processes these signals in a statically optimal fashion, reproducing the rules of Bayesian inference. It was also proposed that the Bayesian based processing uses the statistics of natural head movements. The outputs of semicircular canals and head's angular velocity were assumed to be subjects to Gaussian noise. By using particle filtering, a three dimensional model of vestibular signal processing model was developed based on optimal estimation. The model was successfully tested by computational experiments, as well, it was proved to be efficient in modelling the vestibulo-ocular reflex.

Among the vestibular information processing models mentioned above, the concepts of internal model and estimator or observer are crucial for the system description. Detailed reviews of existing vestibular information processing models can be found in [START_REF] Macneilage | Computational approaches to spatial orientation: from transfer functions to dynamic bayesian inference[END_REF]126]. Interestingly, in robotic systems, the concept of the internal model has been known for decades, since the early works of E. Kalman in linear filtering [START_REF] Kalman | A new approach to linear filtering and prediction problems 1[END_REF] and D. Luenberger in state estimation for linear systems [START_REF] Luenberger | Observing the state of a linear system[END_REF].

Roles of the vestibular system

Humans rely on the multiplicity of sensory inputs and sophisticated anticipatory mechanisms to solve the control problems subserving standing, walking, running, jumping, dancing, and so on. Vestibular inputs play a central role in all these tasks, which are achieved through a combination of postural movements and forces and torques exerted against the environment. Better understanding of the functioning of the vestibular system may have important implications in design and control of robotic systems.

Vision. In humans, the head-located vestibular system is known to participate in a number of functions that include gaze stabilisation through the vestibulo-ocular reflex [START_REF] Berthoz | Differential visual adaptation of vertical canal-dependent vestibulo-ocular reflexes[END_REF][START_REF] Berthoz | Neural correlates of horizontal vestibulo-ocular reflex cancellation during rapid eye movements in the cat[END_REF][START_REF] Berthoz | Adaptive modification of the vestibulo-ocular reflex by mental effort in darkness[END_REF][START_REF] Dieterich | Vestibulo-ocular reflex[END_REF]. The vestibulo-ocular reflex stabilises the gaze to ensure clear and still vision. It is a reflex of eye movement that stabilises the image projected on the retina during head movements. Produced eye movements are in the direction opposite to head movements. The reflex has both rotational and translational components which are driven by semicircular canals and otoliths, respectively.

Self-motion perception. The vestibular system is a key sensory organ that enables perception of body motion [START_REF] Berthoz | Perception of linear horizontal self-motion induced by peripheral vision (linear vection) basic characteristics and visualvestibular interactions[END_REF]. A human with a healthy vestibular system can always tell if the body is moving even if other senses such as vision, audition are absent. Vestibular system provides us with the ability to distinguish between self-generated motion and the external one. It has been shown that vestibular only information is sufficient to reconstruct current and past passive body locations [START_REF] Israel | Spatial memory and path integration studied by self-driven passive linear displacement. i. basic properties[END_REF][START_REF] Israël | Cortical control of vestibular-guided saccades in man[END_REF].

Balance. The vestibular system plays a dominant role in the coordination of postural reflexes, such as vestibulocollic reflex. The vestibulocollic reflex is responsible for maintaining head and body posture. This reflex stabilises the head with respect to inertial space. It produces commands to move the head in the direction opposite to the direction of the actual velocity of the head [START_REF] Ezure | Frequency-response analysis of vestibular-induced neck reflex in cat. ii. functional significance of cervical afferents and polysynaptic descending pathways[END_REF][START_REF] Baker | Spatial and temporal response properties of the vestibulocollic reflex in decerebrate cats[END_REF]. Another important role of the vestibular system is vestibulospinal reflex which coordinates head and neck movement with respect to the trunk of the body. The goal of the reflex is maintaining the head in an upright position [START_REF] Allum | Afferent Control of Posture and Locomotion[END_REF]. Together, vestibulocollic and vestibulospinal reflexes are responsible for selfbalancing control [145,146,127,[START_REF] Allum | Trunk sway measures of postural stability during clinical balance tests: effects of a unilateral vestibular deficit[END_REF][START_REF] Manchester | Visual, vestibular and somatosensory contributions to balance control in the older adult[END_REF].

Perception of verticality. The vestibular system is the principal sensory system which is able to perceive perceive gravitational forces. When the body is motionless, otoliths measure the gravitational acceleration vector, whose components render the sense of absolute verticality [START_REF] Bisdorff | The perception of body verticality (subjective postural vertical) in peripheral and central vestibular disorders[END_REF]149]. Knowledge of gravitational verticality is essential for balancing and posture control, as it allows to determine spatial orientation of the body [START_REF] Chase | Semantics in the perception of verticality[END_REF].

Frame of reference. The vestibular system, like embodied inertial sensors, provides the CNS with a head-centred frame of reference. It may be suggested that low-level balance and posture control is realised in this frame of reference. Spatial transformations from head-fixed and world inertial frame can be performed based on vestibular system measurements. Therefore, this embodied frame of reference is directly related to the world inertial frame and enables the neural system to perform stable posture control independently from other sensory inputs, such as tactile or proprioception information on ground inclination. In this way, ground-independent posture and balance control can be implemented.

Head stabilisation behaviour in animals and humans

Various human motion experimental studies showed that humans stabilise their heads while performing locomoting, balancing or other postural tasks. It has been initially proposed by T. Pozzo and A. Berthoz that humans stabilise their heads in rotation for different locomotor tasks, such as free walking, walking in place, running in place and hopping [115]. In the experiments with ten healthy subjects humans stabilised their heads in such a way as the maximum angular amplitude of Frankfort's plane (plane of horizontal semicircular canals) did not exceed 20 • . It was suggested that such stabilisation is probably due to a cooperation between both the measurement of head rotations by the semi-circular canals and the measure of translations by the utriculus and sacculus (otolith organs). The plane of the stabilisation is determined by the task; it can vary and be controlled by gaze. Further experiments showed that total darkness does not significantly influence the stabilisation of the head, which stresses the importance of this behaviour in the coordination of the multiple degrees of freedom of the body during gait [116].

Later in [117], it was shown that head stabilisation occurred also in the frontal plane during the maintenance of monopodal and bipodal equilibrium on unstable rocking platforms. The head remained stable relative to the vertical, despite large translations in the frontal plane. Head angular stabilisation close to vertical orientation was essential for effective postural control during those complex balancing tasks. Some recent behavioural studies by A. Berthoz and colleagues showed that head orientation is anticipated during locomotion relatively to walking direction [START_REF] Grasso | Eye-head coordination for the steering of locomotion in humans: an anticipatory synergy[END_REF]113,[START_REF] Hicheur | Head motion in humans alternating between straight and curved walking path: combination of stabilizing and anticipatory orienting mechanisms[END_REF]. This may suggest that head orientation and gaze stabilisation is important for motion planning during locomotion, and both visual and vestibular cues can be processed by the CNS in a better way if the head is stabilised and oriented towards the walking direction. Additional studies suggested that the motion of the head, together with gaze control, is closely related to optimal postural control during locomotion [START_REF] Arechavaleta | An optimality principle governing human walking[END_REF].

In [START_REF] Keshner | Predicting control mechanisms for human head stabilization by altering the passive mechanics[END_REF], a control mechanism model for head stabilisation was described. Angular velocities of the head and trunk in space were recorded in seated subjects during external perturbations of the trunk. The passive mechanics of the head was changed by adding additional mass in different experimental trials. It was shown that head stabilisation in a horizontal plane in yaw orientation did not differ much with respect to the changed inertia of the head. For pitch motion, the response of the head-neck stabilisation controller was changed when additional mass was added to the head. However, in all the cases subjects were stabilising their heads while their trunk was perturbed.

In [START_REF] Buchanan | Vestibular loss disrupts control of head and trunk on a sinusoidally moving platform[END_REF], balancing on a moving platform with subjects with and without the bilateral vestibular loss was studied. Results showed that subjects with vestibular loss were unable to perform that task properly, and their trunk and head were not stabilised in space, while healthy subjects were stabilising their heads regardless to the motion of the platform.

Similar to humans, head stabilisation was observed in many other animals. For instance, head stabilisation was reported for cats [START_REF] Goldberg | Reflex and mechanical contributions to head stabilization in alert cats[END_REF]. Similar head stabilisation was found in monkeys during locomotion [148]. The head was stabilised and absolute values of pitch and roll head movements did not exceed 7 • . The similar result was obtained for running monkeys [START_REF] Dunbar | Stabilization and mobility of the head and trunk in wild monkeys during terrestrial and flat-surface walks and gallops[END_REF]. For horses, a weaker head stabilisation effect was reported [START_REF] Dunbar | Stabilization and mobility of the head, neck and trunk in horses during overground locomotion: comparisons with humans and other primates[END_REF].

Head stabilisation was observed for birds, as well. In [START_REF] Green | Head orientation and trajectory of locomotion during jumping and walking in domestic chicks[END_REF], head stabilisation in chickens during jumping and walking on surfaces of different slopes. Results suggested that the head was stabilised during locomotion but the angle of stabilisation increased with increasing downwards slope of the walking surface and decreased with increasing upwards slope. Head stabilisation was reported for other birds such as herons, as well [START_REF] Katzir | Head stabilization in herons[END_REF]. In most of the cases, different types of herons stabilised their heads' spatial orientation and location while their body was disturbed by harmonic oscillations. Head bobbing during locomotion is a very well-known behaviour for birds like pigeons, egrets, whooping cranes [START_REF] Frost | The optokinetic basis of head-bobbing in the pigeon[END_REF][START_REF] Davies | Head-bobbing during walking, running and flying: relative motion perception in the pigeon[END_REF][START_REF] Cronin | Head-bobbing behavior in walking whooping cranes (grus americana) and sandhill cranes (grus canadensis)[END_REF][START_REF] Fujita | Head bobbing and the body movement of little egrets (egretta garzetta) during walking[END_REF]136]. Head-bobbing behaviour results in stabilisation of the head to the surroundings for specific phases of the locomotion cycle. This bobbing is coupled with the locomotion and is mainly under the control of visual system inputs [START_REF] Frost | The optokinetic basis of head-bobbing in the pigeon[END_REF]106].

In the studies mentioned above, it was shown that orientation of the head is naturally stabilised during locomotion, balancing. These studies emphasized the importance of head stabilisation as a part of the general postural control in humans and animals. In some cases, head stabilisation may be related to the task performed by a human, but naturally, the head stabilisation may be the result of vestibular-ocular interactions, as well [START_REF] Guitton | Visual, vestibular and voluntary contributions to human head stabilization[END_REF]. However, in all of these cases vestibular information is important for the head-neck control system, and sometimes it is the only source of information available [START_REF] Bronstein | Evidence for a vestibular input contributing to dynamic head stabilization in man[END_REF]. One of the key roles of head stabilisation is related to the establishment of a stable reference frame in which spatial perception, multiple sensory integration, and postural control are performed. The stable frame of reference based on vestibular information provides the brain with a mobile reference frame, which, in cooperation with vision and gaze allows a 'top-down' control of locomotion [START_REF] Bernardin | Gaze anticipation during human locomotion[END_REF][START_REF] Authie | Differences in gaze anticipation for locomotion with and without vision[END_REF]. [START_REF] Ang | Nonlinear regression model of a low-g MEMS accelerometer[END_REF] Sensing motion in robots with inertial sensors

Inertial sensors

In robotic systems, inertial sensors play a role similar to the vestibular system in humans and animals. In this subsection, we give a short introduction to inertial sensors and their applications in robotic systems. Modern inertial sensors are electromechanical transducers which measure translation and rotation of their bodies. Recent technological developments provided robotics with various types of inertial sensors [START_REF] Barbour | Inertial sensor technology trends[END_REF]144]. The most common inertial sensors are accelerometers, gyrometers and inclinometers. Very often they are combined together and then they are called inertial measurement units (imu).

An accelerometer measures linear acceleration which is a result of linear forces and gravitational forces applied. Modern accelerometers are usually implemented in MEMS based electronic circuits and can have sensitivity in one, two or three axes. Some examples of different technologies used in accelerometer design can be found in [START_REF] Lapadatu | Dualaxes capacitive inclinometer/low-g accelerometer for automotive applications[END_REF][START_REF] Ang | Nonlinear regression model of a low-g MEMS accelerometer[END_REF]108,[START_REF] Bums | Resonant microibeam accelerometers[END_REF]118]. In a typical accelerometer, a rigid body is constrained to linear translation inside the frame of the sensor. The body is attached to the frame with a spring of a known stiffness. Assuming linear stiffness, low friction and small displacements acceleration of the sensor's body can be calculated from the body's displacement. Importantly, accelerometers react to both translational and gravitational accelerations. In absence of translational motion, they can thus be used as tilt meters (inclinometers). However, this causes a significant problem for acceleration sensing in robotics which is often called gravito-inertial ambiguity. It is impossible to distinguish between translational and gravitational components of acceleration when a robotic body is being accelerated in translation and rotation at the same time.

An inclinometer is a sensor used to measure the absolute angular orientation of a body with respect to gravitational acceleration. The physical principle of sensing is the same as for the accelerometer, but an inclinometer's primary function is to measure angular orientation with respect to the gravitational acceleration vector. A very simple type of inclinometer can be implemented with a pendulum which tends to keep its verticality, and in steady state, it is aligned with the gravitational acceleration vector. The measurement is an angle between the pendulum and the frame of the sensor. This angle is usually measured by magnetic, optical or electromechanical angular encoders attached to the joint between the sensor frame and the pendulum. Usually, a moving body in an inclinometer is damped to achieve convergence and steady measurements. In the cases when the frame of the sensor is accelerated, the measurement from the inclinometer is no longer tilt-only related, and the sensor behaves in the same way as the tilted accelerometer as it responses both to translational and gravitational acceleration. Modern inclinometers use different electromechanical, magnetic, hydraulic, optical and other physical effects. Some design examples can be found in [102, [START_REF] Manaf | One-side-electrodetype fluid-based inclinometer combined with cmos circuitry[END_REF][START_REF] Lin | High-performance inclinometer with wide-angle measurement capability without damping effect[END_REF]150].

A gyrometer (or a gyroscope) is a sensor for measuring the angular velocity. Modern gyrometers, similar to accelerometers are implemented in electronic circuits based on MEMS technology [START_REF] Greiff | Vibrating wheel micromechanical gyro[END_REF]105]. A common MEMS based gyrometer measures angular velocity by means of Coriolis acceleration [START_REF] Geen | Rate-sensing gyroscope[END_REF].

Verticality estimation methods

Verticality estimation is a crucial task for the stability of mobile robotic systems. In particular humanoid robots and other walking machines require accurate knowledge of verticality to perform balancing and postural tasks in the gravitational field. In this subsection, we look into some basic methods of verticality estimation methods used in robotic systems. Here we limit our review to approaches which use inertial measurements only. Theoretically, simple time integration of gyrometers output will provide us with the angular orientation of a body (robot) in space. However, initial conditions have to be known, which is not the case for many real-life applications. Another problem with rate sensors is bias, which changes with time, temperature and other conditions. An accelerometer can be used as a tilt sensor to measure the vertical orientation of the robot in the cases when the linear acceleration of the robot is zero or negligible. But most of robotic systems such as humanoid robots are moving continuously with variable velocities and are the subjects to unpredictable mechanical impacts. Generally speaking, inertial sensors are noisy because they pick-up vibrations that become added to the low-frequency components of interest of the acceleration and velocity signals. Gyroscopic measurements also suffer from bias and are highly sensitive to dynamic errors. To combat these problems, different ap-proaches to the design state observers and sensor fusion methods have been proposed to improve inertial measurements [START_REF] Barshan | Inertial navigation systems for mobile robots[END_REF].

In [START_REF] Ang | Nonlinear regression model of a low-g MEMS accelerometer[END_REF], a nonlinear regression model to improve the accuracy of a low-g MEMS accelerometer was proposed. It was assumed that accelerometer was not translated and its measurements provided the tilt information only. Similarly, in [119] accelerometer was used as a tilt sensor. Accurate tilt sensing was achieved with a linear kinematic model which included scale factor, bias and misalignment. It was assumed that the body does not perform any translational motion which makes this approach limited to rotations only. Gyrometer and accelerometer measurements were used together with a Kalman filter for sensors alignment and calibration errors compensation in [START_REF] Grewal | Application of kalman filtering to the calibration and alignment of inertial navigation systems[END_REF]. Similar to previous cases only rotations were considered.

The vertical orientation of a flying robot was estimated in [START_REF] Baerveldt | A low-cost and low-weight attitude estimation system for an autonomous helicopter[END_REF]. The measurement system included an inclinometer and a rate gyro. The data coming from the sensors was fused through a complementary filter, which compensated the slow dynamics of the inclinometer. It was assumed that the robot did not perform fast accelerated motions.

A sensor fusion approach for verticality estimation in mobile robots which are translated and rotated simultaneously was proposed in [138]. To resolve the ambiguity of translational and gravitational components in measurements the odometry of the mobile robot was used. Angular measurements from the robot's wheels, joints and knowledge of its kinematics were used to provide the estimator with additional information about the robot's orientation.

In [120] drift-free attitude estimation for accelerated rigid bodies was described. The attitude estimation problem for an accelerated rigid body using gyros and accelerometers was solved with a switching algorithm which employed Kalman filters. Switching was performed based on the values of estimated linear acceleration of the body. The main idea of the algorithm was to consider the translational accelerations as disturbances that were measured partially by the accelerometer. When the acceleration of the body was too high, the accelerometer measurements were considered completely unreliable to provide verticality measurements switching algorithm forced the estimator to rely on the rate gyros by setting the accelerometer noise covariance matrix to infinity.

Additional inclination sensor was used in [START_REF] Leavitt | High bandwidth tilt measurement using low-cost sensors[END_REF]. A state estimation technique was developed for sensing inclination angles using a low-bandwidth tilt sensor along with an inaccurate rate gyro and a low-cost accelerometer. The model of rate gyro included an inherent bias along with sensor noise. The tilt sensor was modelled as a pendulum and was characterized by its own slow dynamics. These sensor dynamics was combined with the gyrometer model to achieve highbandwidth measurements using an optimal linear state estimator. Acceleration of the system in the inertial frame was measured by additional accelerometer and was considered as a known input for the estimator. However, in many robotic systems knowledge of the acceleration vector expressed world inertial frame is unavailable or requires additional global measurements.

In [START_REF] Euston | A complementary filter for attitude estimation of a fixed-wing uav[END_REF] acceleration of an unmanned aerial vehicle expressed in the world frame was estimated by an airflow sensor. This estimation together with the raw measurement from accelerometer was used to calculate the gravitational component of the acceleration. But the performance of the air flow sensor and may not be suitable for human-like walking robotic systems.

A multiple accelerometer based sensory system was used for attitude estimation of a rigid body in [135]. A set of accelerometers was attached to various locations of a rigid body and an optimal linear estimation algorithm was developed for determining pitch and roll of the body fixed at a pivot. The estimated tilt angles values were filtered based on additional angular velocity measurements.

As shown above, the attitude estimation problem for robotic systems is a complex one and often requires nonlinear state estimation techniques to solve it [START_REF] Crassidis | Survey of nonlinear attitude estimation methods[END_REF]. One of the key problems in verticality estimation based on inertial sensors only is the ambiguity in acceleration or inclinometer measurements. Additional techniques are required to separate the gravitational component of acceleration from translational one. In many cases, extra sensors may facilitate the solution. For example, global positioning system (GPS) was used in [START_REF] Gebre-Egziabher | A low-cost gps/inertial attitude heading reference system (ahrs) for general aviation applications[END_REF]; magnetic field sensors were utilized in [103,[START_REF] Fourati | A nonlinear filtering approach for the attitude and dynamic body acceleration estimation based on inertial and magnetic sensors: bio-logging application[END_REF], additional bearing information was required in [START_REF] Baldwin | A nonlinear observer for 6 dof pose estimation from inertial and bearing measurements[END_REF]; landmark measurements were used in [141], Earth horizon sensor was utilized in [START_REF] Grassi | Attitude determination and control for a small remote sensing satellite[END_REF], active vision system was employed in [START_REF] Bras | A nonlinear attitude observer based on active vision and inertial measurements[END_REF]. In humanoid robots, it was shown that inertial sensing can be efficiently used to estimate the robot's attitude when combined with body joint and links relative position sensors and legs contact information [START_REF] Benallegue | Humanoid flexibility deformation can be efficiently estimated using only inertial measurement units and contact information[END_REF]123] or based on additional information from an external range sensor [START_REF] Fallón | Drift-free humanoid state estimation fusing kinematic, inertial and lidar sensing[END_REF]. Like robotic systems, living creatures are solving the same problem of estimation gravitational verticality using a limited set of sensors.

5 Anthropomorphic head stabilisation in human-like robots

Location of inertial sensors in humanoid robots

In living creatures, past and present, the vestibular system is located in the head which is explained by their evolutionary development and specific roles of vestibular organs. In robotic systems, a common design wisdom wants that the inertial sensors to be located close to the centre of mass of a humanoid robot. Most of the humanoid robots have their IMU located in the main body close to their centre of mass. Locating an imu close to the centre of mass provides information about the motion of the centre of mass, of rotations about it, and allows the application of simple models (inverted pendulum) for locomotion and balancing control tasks. In Table 5.1, we summarised our survey results on the location of inertial sensors in some of the humanoid robots used in research.

As we can see from the table, most of the robots have their IMU, or, we may call it, artificial vestibular system, in the main body: between hip joints, torso, trunk or pelvis. Only some robots have their imu located in the head. In robots like Cog, [START_REF] Brooks | The cog project: building a humanoid robot[END_REF], and iCub, [137], the IMU is located in their heads. However, the original design of these robots did not include locomotion functionality, since they were mainly used for human-robot interaction and computational neuroscience studies. The ARMAR-III robot, [START_REF] Asfour | Toward humanoid manipulation in human-centred environments[END_REF], has its inertial sensors in the head, but the lower body of the robot is based on a wheeled platform, which makes it very different from legged biological systems. To our knowledge, very few physical humanoid robots use inertial sensors in the head for posture control during locomotion and balancing. Another example, the CB humanoid, [START_REF] Cheng | Cb: a humanoid research platform for exploring neuroscience[END_REF][START_REF] Hale | Full-body compliant human -humanoid interaction: Balancing in the presence of unknown external forces[END_REF], uses two IMUs: one in the head and another one in the torso. Information from both of them is used to coordinate eyes, head and torso movements [132]. In [START_REF] Kryczka | Implementation of a human model for head stabilization on a humanoid platform[END_REF] and [START_REF] Falotico | Head stabilization based on a feedback error learning in a humanoid robot[END_REF], robotic heads were equipped with IMUs which were used for head stabilisation during locomotion. In [START_REF] Kryczka | Implementation of a human model for head stabilization on a humanoid platform[END_REF], direct measurements of the head's angular orientation were fed back to linear control of the head. However, the performance of this head stabilisation system was quite low, because there were no filtering or estimation methods used for sensory data processing. In [START_REF] Falotico | Head stabilization based on a feedback error learning in a humanoid robot[END_REF], a feedback learning algorithm was employed to stabilise the head orientation independently from the trunk motion. A neural network was used to learn the unknown head dynamics. More recent robotic systems used imu located in the head for cooperative headneck movements and gaze control, which enabled the humanoid robot to achieve human-like gaze and head control behaviour.

Head stabilisation in robots

In robotic systems, inertial sensors provide control systems with important information on actual robot's state such as its body's acceleration, velocity, orientation. This information is important for maintaining stable motion while performing a required task. Accelerometers are often utilized as tilt sensors and gyroscopes are used to measure the change in the robot's orientation. Next, we describe some of the robotic applications in which head stabilisation plays an important role to achieve better performance and human-like behaviour.

Balancing and walking. Classical humanoid robot locomotion strategy is based on zero moment point (ZMP) control originally proposed by M. Vukobratovic [143]. In this case, knowledge about the robot kinematic configuration and mass distribution was sufficient for stable locomotion. Modern humanoid robotics requires robots to move faster and perform more dynamic tasks which require the use of additional sensory information, such as inertial measurements to enhance balance control of the robot.

For example, in [133], development of AAU-BOT1 humanoid robot is described. In this robot, an IMU was placed in the trunk and was used for balance control during locomotion. The orientation of the robot measured by accelerometers and gyroscopes and foot-ground force reactions measured by force sensors were considered to be the dominant information for walking controller.

Tilt and angular velocity of humanoid's torso were used for balance and walking control in [START_REF] Kim | Experimental realization of dynamic walking of the biped humanoid robot khr-2 using zero moment point feedback and inertial measurement[END_REF]. Tilt was measured by accelerometers attached to the torso of the robot. Direct measurements were used by torso roll and pitch controller and predicted motion controller to avoid tilt over situations.

Inertial measurement unit was used for humanoid balance control in [START_REF] Cheng | Cb: a humanoid research platform for exploring neuroscience[END_REF][START_REF] Hale | Full-body compliant human -humanoid interaction: Balancing in the presence of unknown external forces[END_REF]. Three-axis accelerometer and gyro were attached close to the centre of mass in the trunk of the robot. Angular velocity information was used for the centre of mass measurement and calculation of the desired ground interaction force direction for maintaining a stable posture.

Balance control of humanoid robot was described in [START_REF] Chang | Balance control in whole body coordination framework for biped humanoid robot mahru-r[END_REF]. The robot's body was equipped with an IMU for measuring trunk's angular velocity and orientation in space. This information was used for the robot's actual posture calculation together with the measurements from joint sensors.

Biologically inspired postural and reaching control for the humanoid robot was presented in [134]. A humanoid robot was equipped with accelerometer and gyrometer in the head. Normal and tangential contact forces between the robot and the platform were measured by force sensors. Unlike in most of the humanoid research literature, in [134], the platform's (ground's) non zero inclination was considered to be unknown. Unknown ground tilt and disturbance forces were estimated based on measurements from accelerometer and gyrometer. Estimation was implemented by Kalman filtering. It was claimed that inertial sensors and their signals processing could be called as the artificial vestibular system of the humanoid robot [134]. In [114] a sophisticated version of imu and eye control integration was presented for a humanoid robot. The system was based on coordinated human-like control of head-neck and gaze system which enabled to achieve natural saccadic movements in the head's frame of reference.

Gaze and head stabilisation. In many recently developed human-like robots, the vestibulo-ocular reflex is realised for gaze stabilisation. Common human-like robot's head is equipped with two video cameras. Stereo information from these cameras is used for robot's localization and visual perception of the environment. For instance, it may be very important for planning grasping tasks. This visual flow should be stabilised by implementation gaze stabilisation like it is done in biological systems. In addition, this gaze stabilisation behaviour makes a humanoid robot's more natural and realistic which is important in human-robot interaction scenarios.

One of the first humanoid ocular motor control systems was described in [128,129]. A biomimetic gaze stabilisation based measurements from three gyros in the head of the robot was implemented. Feedback-error learning algorithm with neural networks was implied to achieve human-like vestibulo-ocular and optokinetic reflexes. Similarly, in [110], the humanoid robot's head was equipped with an IMU and video cameras. Measurements from the IMU and analysis of visual flow from cameras were used for achieving efficient visual stabilisation. Inertial sensors provided short latency measurements of rotations and translations of the robot's head. Visual flow information provided a delayed estimate of the motion across the image plane. A self-tuning neural network was used to learn to integrate visual and inertial information and to generate proper ocular-motor control signals.

Vision only based gaze stabilisation was presented in [START_REF] Gay | Predictive gaze stabilization during periodic locomotion based on adaptive frequency oscillators[END_REF]. Adaptive frequency oscillators were used to learn the frequency, phase and amplitude of the optical flow from the robot's cameras during locomotion. The developed vision-based control was used for gaze stabilisation during periodic locomotion and for visual object tracking.

In [START_REF] Cheng | Cb: a humanoid research platform for exploring neuroscience[END_REF], a three-axis gyrometer and an accelerometer in the head of the humanoid were used for controlling the gaze and implementing visual attention system. In [START_REF] Lopes | Biomimetic eye-neck coordination[END_REF], biomimetic eye-neck coordination control was proposed and used for visual target tracking. Proprioceptive feedback from neck joints and vestibular signals from inertial sensors in the head were processed together. The control system was tested with the iCub humanoid robot.

6 Benefits of head stabilisation in robots 6.1 Towards a robotic vestibular system

In the previous section, we have presented some example of robots with imus located in their heads. We can call such imus as a robotic vestibular system. In fact, in humanoid robotics research, the term robotic vestibular system or artificial vestibular system was already in use. However, strictly speaking not in all of the cases inertial sensors may be interpreted as the artificial vestibular system because of the ways the sensors are implemented or used. In [142], one of the first attempts to design artificial vestibular system was presented. It was suggested to integrate bi-axial accelerometer and uni-axial gyrometer in a single inertial sensing unit. Later, in [109] a three-axial artificial vestibular system was described. It included a sensing unit with three orthogonal planes. Each plane was equipped with MEMS based accelerometer and gyrometer. Design approaches described in [142] and [109] are similar to the one used in classical sensor engineering when a set of individual inertial sensors were integrated together in a single IMU. An attempt to realise a biomimetic angular rate sensor based on the biomechanical model of the semicircular canals was presented in [START_REF] Ciaravella | Biomechanical modeling of semicircular canals for fabricating a biomimetic vestibular system[END_REF]. However, no further experimental results were presented. A more general point of view to the artificial vestibular system as a part of a multi-sensory system for a robotic rat was presented in [104]. A more thorough example of an artificial vestibular system implementation can be found in [114] where mutual integration of imu sensing and head control for natural gaze control for was demonstrated for a humanoid robot.

Advantages of head stabilisation in human-like robots

A stabilised robotic head would presumably benefit from the same advantages as those of natural heads, hence we suggest that humanoid robots should also adopt a similar head stabilisation behaviour. Head stabilisation improves sensing robustness of visual and vestibular organs located in the head. It is important for the visual sensory system and gaze stabilisation, as well as it enables the establishment of a stable frame of reference for motion planning within the robots' body.

Among numerous other potential advantages, it is important to mention that a horizontally stabilised head facilitates the estimation of the gravitational vertical during locomotion. Knowledge of the direction of the gravity vector, that is of the gravitational vertical, is essential to achieve stance and locomotion as the gravitational vertical may be poorly estimated from visual cues or based on the kinematic relationship of the robot to the ground. However, when accelerometers cannot distinguish between translational and gravitational components of acceleration when translated and tilted at the same time. We suggest that a stabilised robotic head may improve the quality of inertial measurements of the sensors located in this head. First of all, we suppose that the head stabilised independently from the motion of the trunk will be less affected by external forces and disturbances which may occur during locomotion [START_REF] Farkhatdinov | On the benefits of head stabilization with a view to control balance and locomotion in humanoids[END_REF][START_REF] Farkhatdinov | Modeling verticality estimation during locomotion[END_REF]. Second, if the head is stabilised in upright vertical position, then at least one of the axis of inertial sensors will be aligned with gravitational acceleration. This means that a simpler estimation method can be used to process the measurements from inertial sensors, such as accelerometers. In certain situations, it may be assumed that accelerometer located in the upright stabilised head will measure independently gravitational and translational components of acceleration. However, stabilisation of a robotic head with respect to the gravitational verticality requires knowledge of this verticality, and in our case, the only available information related to gravitational verticality can be obtained from inertial sensors, in particular from an accelerometer. This means that the control loop has to be closed by the feedback of the measured or estimated vertical orientation of the head. As a result, we obtain an observer-based closed loop control system. The task of the observer is to estimate the vertical orientation of the head based on inertial sensor measurements without the explicit knowledge of translational acceleration of the head. Hence, our head observation-stabilisation system can be considered as self-sufficient or in other words ideothetic.

Idiothetic sensing, or sensing entirely based on states measured with reference to one's own body, is of course not special to robots. In aerospace engineering, flying and rocketing vehicles also use imu. Long ago, it was noticed that guidance was greatly simplified if the inertial sensors were placed on stabilised platforms [START_REF] Duncan | Inertial guidance, navigation , and control systems[END_REF]. In such systems, the application of fundamental mechanical principles and stabilising control provided engineers with possibilities to establish the gravity referenced Earth's inertial frame without the need for other external references. Ideothetic inertial sensing can be useful to any type of mobile robotic systems [START_REF] Barshan | Inertial navigation systems for mobile robots[END_REF].

Recently, a concept of top-down control was proposed for humanoid robotics. It was suggested the posture control during locomotion is governed in the head's frame of reference. As the head is stabilised, a stable frame of reference is achieved. Inertial measurements from the vestibular system would be expressed in this frame of reference and would be used for gaze control. Gaze direction anticipates on head orientation which in turn anticipates on the body segments during locomotion [START_REF] Kadone | Gaze anticipation during human locomotion -top-down organization that may invert the concept of locomotion in humanoid robots[END_REF][START_REF] Laumond | The words of the human locomotion[END_REF][START_REF] Bernardin | Gaze anticipation during human locomotion[END_REF] and this behaviour can be used to control steering in assistive walking robots [START_REF] Farkhatdinov | Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance[END_REF]. Following the top-down control organisation, a humanoid robot can be controlled in its stabilised head's frame of reference as it was done in [130,[START_REF] Hashimoto | Realization of biped walking on soft ground with stabilization control based on gait analysis[END_REF]. In [130], the humanoid robot was teleoperated and its desired walking direction and posture were given to the controller in head's frame. This example of robot control with top-down organization differs from the classical humanoid locomotion control when posture configuration was defined in the world (ground) reference frame. In most of the humanoid walking applications ground is assumed to be flat and rigid, and its inclination has to be known. However, the concept of top-down control organization suggests that the only information which is required is joint (proprioceptive) information of the robot's body with respect to a stabilised head's frame of reference. Head stabilisation also contributes to whole body dynamic stabilisation during locomotion in humanoid robots, as it was demonstrated in [START_REF] Laumond | The yoyo-man[END_REF]. Interestingly, head stabilisation contributed to the stabilisation while the head's mass accounted only for 7% of the total mass of the body.

Current state of research and challenges

In this final subsection, we would like to re-iterate the importance of head stabilisation for robots through demonstrating some successful implementations. Research on human-like head stabilisation and control has been intensified over last years. In [114] a set of experiments for human-like gaze control for a humanoid robot was presented. Efficiently coordinated head and eye movements were achieved through the development of anthropomorphic algorithms based on the head's imu measurements and position sensing of head-neck and headeye electric motors. Experiments with Romeo humanoid robot demonstrated that eyes-only, head-only and combined head-eye coordinated movements corresponded to the natural behaviour observed in humans, which in turn contributed to realistic and intuitive human-robot interaction.

The problem of compensating for disturbances induced in a humanoid robot's cameras due to self-generated body movements was approached in [122]. The head's angular velocity measured by an embedded imu was used to compensate the head's and the eyes' movements, which improved the quality of the robot's optical flow.

An internal model-based adaptive gaze stabilisation for a humanoid robot was proposed in [140]. The internal model was based on the coordination of vestibulocollic and vestibulo-ocular reflexes, and it includes a self-learning and adaptation capabilities. As a result, the experiments with a simulated robotic platform demonstrated that the model was able to stabilise the robot's head independently of the torso movements and at the same time to control gaze for tracking visual targets.

Three head stabilisation control approaches for humanoid robots were described and implemented in [START_REF] Falotico | Head stabilization in a humanoid robot: models and implementations[END_REF]. The approaches were two types of inverse kinematic based control and bioinspired adaptive control based on feedback error learning control. All controllers used the robot's head imu measurements and head-neck joint kinematics information. Additionally to head stabilisation behaviour, vestibulo-ocular and optokinetic reflexes were implemented for the gaze control. Control based on feedback error learning adjusted the mapping of sensory errors into control errors. It showed better performance in head stabilisation behaviour compared to a simple feedback control with inverse kinematics model, demonstrating that nonlinear adaptive techniques are more suitable for anthropomorphic robot control.

Whereas significant progress has been achieved in transferring anthropomorphic behaviours to humanoid robot control, substantial research and development challenges remain. Firstly, resolution of gravito-inertial ambiguity for inertial sensor measurements is problematic for robots with ideothetic sensing and very often employment of external sensors with a fixed frame of reference is required. One more challenging issue, also related to gravito-inertial ambiguity is the existence of several competing gaze-head stabilisation approaches, however, due to technical limitation none of them is mimicking the simplicity of the biological system and achieve sufficient performance. Further development of gaze stabilisation algorithms will also require integration of visual flow based movement compensation, so that accurate visual tracking is achieved while head and gaze are stabilised. Addressing these challenges will enable development of more dynamic, stable and reliable robotic systems, and will be beneficial not only to humanoid robots but also to other types of mobile systems, such as jumping and flying robots.

Fig. 1 .

 1 Fig. 1. The vestibular organs located in each inner ear (A). Main organs are three almost orthogonal semicircular canals (superior, posterior and lateral) and two otolith organs (utricle and saccule). Semicircular canals measure angular velocity of the head (B). Otolith organs measure linear gravitoinertial acceleration (C).

Table 1 .

 1 Location of the inertial sensors in the humanoid robots

	Robot's name	imu location Reference Year
	Cog	head	[24]	1999
	asimo	upper body [124, 74] 1999
	atlas (DASL-1) pelvis	[79]	2002
	h7	upper body [81]	2004
	khr-3 hubo	torso	[112]	2005
	fhr-1 fibo	hip	[147]	2006
	khr-2	torso	[85]	2006
	cb	head & torso [31, 71]	2007
	iCub	head	[137, 111] 2007, 2012
	mahru-r	pelvis	[29]	2008
	armar-iii	head	[7]	2008
	Lola	upper body [27, 93]	2009
	Nao	torso	[62]	2009
	aau-bot1	trunk	[133]	2009
	Sarcos Primus hip	[131]	2010
	kobian	head	[86]	2012
	wabian	head	[49]	2012
	romeo	head	[114]	2014
	coman	waist	[1]	2014
	momaro	head	[125]	2016

Acknowledgment I. Farkhatdinov was supported by a fellowship from Ecole Doctorale, Sciences Mécaniques, Acoustique, Electronique et Robotique de Paris (UPMC). Additional funding was provided by the European Research Council, Advanced Grant PATCH, agreement No. 247300 and EU FP7 BALANCE (ICT-601003).


Jacqueline Vaissière
email: jacqueline.vaissiere@univ-paris3.fr-

Philippe Boula

Philippe Boula De Mareüil
email: philippe.boula.de.mareuil@limsi.fr-

Identifying a language or an accent: from segments to prosody

come

INTRODUCTION

Everyday life experience shows that, in some cases, it is possible to identify a language or to determine the origin of an accent, by recognising relevant features. To what extent are naive listeners able to identify various languages or accents, and how to measure it quantitatively? To answer that question, the key difficulty is that certain parameters may be distinctive to certain listeners (for example locals) but not to others.

The following questions also deserve attention. What characterises a language or an accent physiologically, acoustically and perceptually? Does the identification rely more on the phonemic content and on the instantiation of co-articulation phenomena, on voice quality, on filled pause and hesitation phenomena, melodic clichés, pitch range, pitch level at phrase boundaries, durational profiles, stress location errors or other shibboleths, which are interpreted as "foreign"? Although the question is interesting from a practical and theoretical viewpoint, scientific publications hosted only little debate over the contribution of intonation to the perception of an accent. Studies even often concentrate on the articulation of the sole vowels (e.g. [START_REF] Harrington | An acoustic study of broad, general and cultivated Australian English vowels[END_REF]. What is more, the combination of pitch changes and the pronunciation of certain phonemes may result in the perception of a language or an accent, while each cue taken separately may not. Our purpose, in the remainder of this paper, is to focus on the relative importance of prosody, to identify a dialectal variety or an accent. Interestingly indeed, many presentations in this workshop approach language variety identification from that angle.

THE ROLE OF PROSODY

The word accent stems from Latin: accentus -ad+cantus, which is a loan translation of Greek (prosôidia) Is it by chance that this term has been chosen to designate both a prosodic prominence and a way of speaking which departs from a norm? The question applies to regional, social and foreign accents [START_REF] Léon | Précis de phonostylistique[END_REF][START_REF] Rossi | L'intonation, le système du français : description et modélisation[END_REF] seems to answer it in the negative, without proving it. In the case of a foreign accent, viewed as the effect of a confrontation of two phonological systems in contact -from a native language (L1) and a target one (L2) -, the mastery of an L2-like prosody may be difficult to teach, from a pedagogical viewpoint, sometimes because teachers themselves are not well aware of their prosodic systems. But also, invariants probably exist, beyond regional differences, between a Parisian and a person from Marseilles speaking English, in the rhotic pronunciation, diphthongisation, vowel reduction, and other constant articulatory habits. [START_REF] Ladd | Intonational phonology[END_REF] for his part relates his experience of an American living in Great Britain 1 : he suggests a more important plasticity of melody, which we can observe in infants in phase of language acquisition. It has been claimed that the characteristic categories of the mother tongue prosody are extracted very early -prior to the lexicon acquisition [START_REF] Konopczynski | L'intonation de question dans le langage emergent[END_REF][START_REF] Mehler | Language and Cognition[END_REF].

As mentioned earlier, it is noteworthy that little space is usually devoted to prosody, somewhat of an 1 Speaking about the impression of condescension or arrogance which certain polite questions may give, Ladd expresses himself in these terms [START_REF] Ladd | Intonational phonology[END_REF]: "As an American speaker resident in Britain I have long since adopted the RP tune for use in these contexts, and now find it rather difficult to switch off. Though my segmental phonetics and phonology are still almost completely American, I have on several occasions elicited chilly reactions in North America unintentionally using the RP tune, which suggests that it is the intonation, not the overall RP package, that Americans hear as condescending". Before him, Bloomfield had been struck by the rising intonation in certain British ways of saying "thank you" [START_REF] Bloomfield | Language[END_REF]. unexplored field even in dialectology. The AMPER (Atlas Multimédia Prosodique de l'Espace Roman) linguistic atlas of Romance languages is promising, though [START_REF] Romano | Un progetto di Atlante geoprosodico multimediale delle varietà linguistiche romanze[END_REF]. So is the TIE network (Tone and Intonation in Europe), the objective of which is threefold: to provide a platform to coordinate European projects in the domain of prosody, to combine intonation and tones (in particular from Serbo-Croatian and languages of immigrant communities like Papiamentu) in the laboratory phonology approach, to analyse European languages and non-standard varieties (Gussenhoven in preparation). Studies especially within the framework of the IViE project (Intonational Variation in English) revealed how certain intonational patterns are specific to some English varieties [START_REF] Wells | Accents of English[END_REF][START_REF] Nolan | Can 'ToBI' transcribe intonational variation in British English?[END_REF][START_REF] Grabe | Modelling intonational variation in English: the IViE system[END_REF][START_REF] Yan | A Comparative Analysis of UK and US English Accents in Recognition and Synthesis[END_REF][START_REF] Fletcher | Intonational variation in four dialects of English: the high rising tune[END_REF]. This is the case with the "high rising terminal tune" (HRT), whether it is semantic or simply realisational in Ladd's classification [START_REF] Wells | Accents of English[END_REF][START_REF] Ladd | Intonational phonology[END_REF]. Often related to the socalled Frequency Code 2 , it is common mainly in narrative texts among young females, who terminate statements like questions, as if a confirmation from the interlocutor were expected, or for checking that the latter follows. A study is also dedicated to the contribution of intonation to the impression of German accent in English and English accent in German [START_REF] Jilka | The contribution of intonation to the perception of foreign accent[END_REF]. Moreover, IViE has inspired a project called Dialektintonation, the first objective of which is to describe prosodic variation across regional dialects in Germany [START_REF] Peters | Identification of regional varieties by intonational cues. An experimental study on Hamburg and Berlin Germans[END_REF]. Likewise, a series of inquiries underlined different stress patterns in patois from the North/North-East of France, and more generally from the whole French-speaking area [START_REF] Carton | Insistance dialectale[END_REF][START_REF] Carton | Les Accents des Français[END_REF]Hintze et al., 2000) 3 . To complete the survey, let us cite a few additional studies on:

-the intonational patterns (especially interrogative) of some Italian varieties [START_REF] Endo | Aspetti dell'intonazione in alcune varietà dell'italiano[END_REF][START_REF] Gili Fivela | Focalizzazione e 'phrasing' nel parlato letto. Analisi di due varietà di italiano[END_REF][START_REF] D'imperio | Perception of questions and statements in Neapolitan Italian[END_REF][START_REF] Marotta | La teoria autosegmentale nell'analisi dell'intonazione interrogativa di due varietà di italiano toscano (Lucca e Siena)[END_REF];

-Peninsular/Latin American Spanish [START_REF] Navarro Tomás | Manual de entonación española[END_REF][START_REF] Garrido Almiñana | Modelling Spanish Intonation for Text-to-Speech Applications[END_REF][START_REF] Quilis | Curso de fonética y fonología españolas[END_REF][START_REF] Sosa | Fonética y Fonología[END_REF][START_REF] Mora | Entonación[END_REF][START_REF] Beckman | Intonation across Spanish, in the Tones and Break Indices framework[END_REF];

2 This HRT is interpreted as iconic, non-arbitrary in some paralinguistic theories based on biological metaphors, according to which small larynxes and vocal cords with fast vibration rates would be manifestations of weakness and submissiveness -e.g. [START_REF] Vaissière | Phonetic Explanations for Cross-Linguistic Prosodic Similarities[END_REF]Gussenhoven in preparation). 3 In dialectally marked ways of speaking, the author notices additional vowel duration in forms such as je vais à Nâncy [ ( )v (z)an :si] ("I'm going to Nancy"), creating a trochaic rhythm which may give the impression of a "stress shift" or "backing", even though he challenges these terms: he rather interprets it as the preparation of a rising-falling contour distributed over two syllables.

-the identification of two dialectal varieties of Scots [START_REF] Van Leyden | Prosody versus segments in the identification of Orkney and Shetland dialects[END_REF];

-the contribution of prosody to the identification of Dutch varieties (van Bezooijen & Gooskens, 1999); -a prosodic typology of Swedish dialects based on pitch accent (of type I or II) [START_REF] Bruce | Phonetics and phonology of the Swedish dialects -a project presentation and a database demonstrator[END_REF]; -tonal accent system in the dialects of Japanese [START_REF] Sugito | 50 Years of Study on Japanese Prosody[END_REF];

-the discrimination between European and Brazilian Portuguese on the basis of prosody [START_REF] Frota | Language Discrimination and Rhythm Classes: Evidence from Portuguese[END_REF];

-the identification of Arabic dialects [START_REF] Barkat | Prosody as a Distinctive Feature for the Discrimination of Arabic Dialects[END_REF][START_REF] Hamdi | Variation rythmique des dialectes arabes, Actes des 24 es Journées d'Étude sur la Parole[END_REF].

The latter study [START_REF] Hamdi | Variation rythmique des dialectes arabes, Actes des 24 es Journées d'Étude sur la Parole[END_REF] as well as the one on Portuguese [START_REF] Frota | Language Discrimination and Rhythm Classes: Evidence from Portuguese[END_REF] were carried out using procedures put forth in [START_REF] Ramus | Rythme des langues et acquisition du langage[END_REF] dissertation, investigating the proportion of vocalic intervals (%V) and the standard deviation of consonantal intervals ( C) to discriminate between different rhythmic classes -especially syllable-timed vs. stress-timed.

One of the weaknesses of those parameters is their sensitivity to tempo changes -suppose an utterance begins slowly and ends quickly. To capture this problem, Grabe proposes to measure the variability in duration between two successive intervals of the same type (vocalic or consonantal), by considering a "Pairwise Variability Index" (PVI) which normalises speech rate variation [START_REF] Grabe | Durational Variability in Speech and the Rhythm Class Hypothesis[END_REF]. Under different speech rate conditions, the PVI approach may be more robust than the %V-C approach, but it yields a continuum rather than a clear cut separation between rhythmic classes.

Other studies attempt to elucidate the role of intonation rather than rhythm. Some of these studies, in addition to those of the TIE, IViE and Dialektintonation projects, are in keeping with the guiding principles of the autosegmental-metrical model of intonation [START_REF] Ladd | Intonational phonology[END_REF][START_REF] Jilka | The contribution of intonation to the perception of foreign accent[END_REF][START_REF] D'imperio | Perception of questions and statements in Neapolitan Italian[END_REF][START_REF] Marotta | La teoria autosegmentale nell'analisi dell'intonazione interrogativa di due varietà di italiano toscano (Lucca e Siena)[END_REF][START_REF] Beckman | Intonation across Spanish, in the Tones and Break Indices framework[END_REF].

Inspired by [START_REF] Pierrehumbert | Synthesizing intonation[END_REF] work used in the ToBI system (TOnes and Break Indices) [START_REF] Silverman | ToBI: a standard for labeling English prosody[END_REF], this theoretical framework is interesting for our issue, in the sense that it assumes autonomous segmental and suprasegmental tiers.

Perceptually too, prosodic clues facilitate human language acquisition: various studies in psycholinguistics demonstrated it, throughout a battery of tasks consisting in decoding sequences of ambiguous words or in segmenting an artificial language [START_REF] Banel | Contribution des indices métriques à l'apprentissage d'un langage artificiel[END_REF]. On the whole, however (with maybe the exception of stress and phoneme duration), the question of the role of prosody in the perception of a (foreign) accent has barely been tackled, as a thorough and recently published state-of-the-art pointed out [START_REF] Piske | Factors affecting degree of foreign accent ina an L2: a review[END_REF]. A model such as [START_REF] Flege | Assessing constraints on secondlanguage segmental production and perception[END_REF] Speech Learning Model (SLM) primarily addresses the notion of phonetic similarity, construction of new perceptual categories for segments and phoneme acquisition -particularly in relatively experienced L2 speakers. [START_REF] Kuhl | Human adults and human infants show a 'perceptual magnet effect' for the prototypes of speech categories, monkeys do not[END_REF] Native Language Magnet (NLM) is also based on segment-sized linguistic units.

As for Best's Perceptual Assimilation Model (PAM), this model mainly describes variation of discrimination between non-native phonemes, depending on their phonetic goodness of fit to native categories [START_REF] Best | Discrimination of non-native consonant contrasts varying in perceptual assimilation to the listener's native phonological system[END_REF].

FINAL REMARKS

Prosody has long been neglected or dismissed, perhaps owing to experimental difficulties, linked to appropriate equipment problems. Speech manipulation and synthesis now allow us to sort out the role of segmental and suprasegmental features in the perception of a language or an accent. Speech synthesis is a good tool to make allowances, since it enables us to monitor a number of parameters: that is the reason why it has been used for delexicalisation and monotonisation purposes [START_REF] Ramus | Language identification with suprasegmental cues: A study based on speech resynthesis[END_REF]. It has been used, together with simulated or altered speech in research on foreign accent [START_REF] Flege | Efects of experience on non-native speaker's production and perception of English vowels[END_REF][START_REF] Pallier | A limit on behavioral plasticity in speech perception[END_REF][START_REF] Magen | The perception of foreign-accented speech[END_REF][START_REF] Jilka | The contribution of intonation to the perception of foreign accent[END_REF].

To obliterate (most of) the segmental structure, lowpass filtered speech is often used -typically at 400 Hz, as if spoken through a thick wall. Nevertheless, this technique entails unnatural stimuli where intelligibility is suppressed, without all the segmental information contained in microprosody being removed.

In addition, it is more difficult to employ with female voices, whose pitch sometimes rises higher than 400 Hz. Consequently, it is not ascertained that the manipulation eliminates any phonemic indication; and that it does not introduce distortions into the perception of prosodic events. Text-to-speech (TTS) synthesis presents fewer drawbacks and is more ecological, since it preserves comprehension.

In several studies of the present workshop, which in return may find applications in automatic language identification, TTS synthesis is regarded as a tool. But it is also of practical and theoretical interest to understand why a synthesis voice is perceived with this or that accent, which can be caricatured.

In this volume, several papers investigate the identification of language varieties or accents. To study prosody separately, independently of segmental properties, the methodology which is proposed by e.g. Gendrot, Lehka, Martin, Romano and Vieru-Dimulescu can apply to the issue of foreign, regional or social accent (e.g. rural vs. urban). But when two forms of the same language are mutually intelligible, the need to be understood is not motivated in the same way [START_REF] Munro | Canadians in Allabama: A perceptual study of dialect acquisition in adults[END_REF]. We come up against the matter of the prestige attached to this or that variety, this or that dialect. Working on languages of comparable status enables us to factor out a whole range of stylistic, historical and social parameters -social class, levelling [START_REF] Armstrong | La variation en français à la lumière de la sociolinguistique[END_REF], etc.