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Section: Research Program

Explicit modeling of speech production and perception

Speech signals are the consequence of the deformation of the vocal tract under the effect of the movements of the jaw, lips, tongue, soft palate and larynx to modulate the excitation signal produced by the vocal cords or air turbulence. These deformations are visible on the face (lips, cheeks, jaw) through the coordination of different orofacial muscles and skin deformation induced by the latter. These deformations may also express different emotions. We should note that human speech expresses more than just phonetic content, to be able to communicate effectively. In this project, we address the different aspects related to speech production from the modeling of the vocal tract up to the production of audiovisual speech. On the one hand, we study the relationship from acoustic speech signal to vocal tract, in the context of acoustic-to-articulatory inversion, and from vocal tract to acoustic speech, in the context of articulatory synthesis. On the other hand, we work on expressive audiovisual speech synthesis, where both expressive acoustic speech and visual signals are generated from text. Phonetic contrasts used by the phonological system of any language result from constraints imposed by the nature of the human speech production apparatus. For a given language these contrasts are organized so as to guarantee that human listeners can identify sounds robustly. From the point of view of perception, these contrasts enable efficient processes of categorization in the peripheral and central human auditory system. The study of the categorization of sounds and prosody thus provides a complementary view on speech signals by focusing on the discrimination of sounds by humans, particularly in the context of language learning.

Articulatory modeling

Modeling speech production is a major issue in speech sciences. Acoustic simulation makes the link between articulatory and acoustic domains. Unfortunately this link cannot be fully exploited because there is almost always an acoustic mismatch between natural and synthetic speech generated with an articulatory model approximating the vocal tract. However, the respective effects of the geometric approximation, of the fact of neglecting some cavities in the simulation, of the imprecision of some physical constants and of the dimensionality of the acoustic simulation are still unknown. Hence, the first objective is to investigate the origin of the acoustic mismatch by designing more precise articulatory models, developing new methods to acquire tridimensional MRI data of the entire vocal tract together with denoised speech signals, and evaluating several approaches of acoustic simulation. This will enable the acoustic mismatch to be better controlled and the determination of the potential precision of inversion to be evaluated in particular.

Up to now, acoustic-to-articulatory inversion has been addressed as an instantaneous problem, articulatory gestures being recovered by concatenating local solutions via the determination of trajectories minimizing some articulatory cost. The second objective is thus to investigate how more elaborated strategies (a syllabus of primitive gestures, articulatory targets…) can be incorporated in the acoustic-to-articulatory inversion algorithms to take into account dynamic aspects.

This area of research relies on the equipment available in the laboratory to acquire articulatory data: articulograph Carstens AG501, head-neck antenna to acquire MRI of the vocal tract at Nancy Hospital, and multimodal acquisition system. Very few sites in France benefit from such a combination of acquisition devices.

Expressive acoustic-visual synthesis

Speech is considered as a bimodal communication means; the first modality is audio, provided by acoustic speech signals and the second one is visual, provided by the face of the speaker. Our research impacts both audiovisual and acoustic-only synthesis fields.

In our approach, the Acoustic-Visual Text-To-Speech synthesis (AV-TTS) is performed simultaneously with respect to its acoustic and visible components, by considering a bimodal signal comprising both acoustic and visual channels. A first AV-TTS system was developed resulting in a talking head; the system relied on 3D-visual data (3D markers on the face, data acquired by MAGRIT team) and on an extension of our non-uniform acoustic-unit concatenation text-to-speech synthesis system (SoJA). An important goal is to provide an audiovisual synthesis that is intelligible, both acoustically and visually. Thus, we continue working on adding visible components of the head through a tongue model where the tongue deformations come from EMA data analysis; and a lip-model to tackle the main recurrent problem of the lack of some lip markers in the 3D data. We will also improve the TTS engine to increase the accuracy of the unit selection simultaneously into the acoustic and visual domains (learning weights, feature selection…).

Another challenging research goal is to add expressivity in the AV-TTS. The expressivity comes through the acoustic signal (prosody aspects) and also through head and eyebrow movements. One objective is to add a prosodic component in the TTS engine in order to take into account some given prosodic entities such as emphasis, in order to highlight some important key words. Expressivity could be introduced before the unit selection step but also by developing algorithms intended to modify the parameters of prosody (in the acoustic domain, and in the visual domain as well). One intended approach will be to explore an expressivity measure at sound, syllable and/or sentence levels that describes the degree of perception or realization of an expression/emotion (audio and 3D domain). Such measures will be used as criteria in the selection process of the synthesis system. To tackle this issue we will also investigate Hidden Markov Model (HMM) based synthesis. The flexibility of the HMM-based approach enables the adjustment of the modeling parameters according to the available data and an easy adaption of the system to various conditions. This point will rely upon our experience in HMM modeling.

To acquire the facial data, we consider using marker-less motion capture system using a kinect-like system with a face tracking software. The software presents a user-friendly interface to track and visualize the motion in real time. Audio is also acquired synchronously with facial data. The advantage of this new system is to acquire rapidly the movements of the face with an acceptable quality. This system is used as an alternative relatively low-cost system to the VICON system.

Categorization of sounds and prosody for native and non-native speech

Discriminating speech sounds and prosodic patterns is the keystone of language learning whether in the mother tongue or in a second language. This issue is associated with the emergence of phonetic categories, i.e., classes of sounds which are related to phonemes, and prosodic patterns. The study of categorization is concerned not only with acoustic modeling but also with speech perception and phonology. Foreign language learning raises the issue of categorizing phonemes of the second language given the phonetic categories of the mother tongue. Thus, studies on the emergence of new categories, whether in the mother tongue (for people with language deficiencies) or in a second language, must rely upon studies on native and non-native acoustic realizations of speech sounds and prosody (i.e., at the segmental level and at the supra-segmental level). Moreover, as categorization is a perceptual process, studies on the emergence of categories must also rely on perceptual experiments.

Studies on native sounds have been an important research area of the team for years, leading to the notion of "selective" acoustic cues and the development of acoustic detectors. This know-how will be exploited in the study of non-native sounds. Concerning prosody, studies are focused on native and non-native realizations of modalities (e.g., question, affirmation, command …), as well as non-native realizations of lexical accents and focus (emphasis). Results aim at providing automatic feedbacks to language learners with respect to acquisition of prosody as well as acquisition of a correct pronunciation of the sounds of the foreign language. Concerning the mother tongue we are interested in the monitoring of the process of sound categorization in the long term (mainly at primary school) and its relation with the learning of reading and writing skills, especially for children with language deficiencies.