Evaluation d'une nouvelle méthode de suivi de formants sur un corpus Arabe

National audienceThis paper develops a formant tracking technique based on Fourier ridges detection. In this method we have introduced a constraint of tracking based on the computation of centre of gravity for a set of frequency formant candidates which leads to connect a frame of speech to its neighbours and thus to improve the robustness of tracking. The formant trajectories obtained by the algorithm proposed are compared to those of a hand edited formant Arabic database, created especially for this work, and those given by Praat with LPC data

An Evaluation of Formant Tracking methods on an Arabic Database

International audienceIn this paper we present a formant database of Arabic used to evaluate our new automatic formant tracking algorithm based on Fourier ridges detection. In this method we have introduced a continuity constraint based on the computation of centres of gravity for a set of formant candidates. This leads to connect a frame of speech to its neighbours and thus improves the robustness of tracking. The formant trajectories obtained by the algorithm proposed are compared to those of the hand edited formant database and those given by Praat with LPC data

Sigma-lognormal modeling of speech

Human movement studies and analyses have been fundamental in many scientific domains, ranging from neuroscience to education, pattern recognition to robotics, health care to sports, and beyond. Previous speech motor models were proposed to understand how speech movement is produced and how the resulting speech varies when some parameters are changed. However, the inverse approach, in which the muscular response parameters and the subject's age are derived from real continuous speech, is not possible with such models. Instead, in the handwriting field, the kinematic theory of rapid human movements and its associated Sigma-lognormal model have been applied successfully to obtain the muscular response parameters. This work presents a speech kinematics based model that can be used to study, analyze, and reconstruct complex speech kinematics in a simplified manner. A method based on the kinematic theory of rapid human movements and its associated Sigma lognormal model are applied to describe and to parameterize the asymptotic impulse response of the neuromuscular networks involved in speech as a response to a neuromotor command. The method used to carry out transformations from formants to a movement observation is also presented. Experiments carried out with the (English) VTR TIMIT database and the (German) Saarbrucken Voice Database, including people of different ages, with and without laryngeal pathologies, corroborate the link between the extracted parameters and aging, on the one hand, and the proportion between the first and second formants required in applying the kinematic theory of rapid human movements, on the other. The results should drive innovative developments in the modeling and understanding of speech kinematics.Comment: Published in Open Acce

Three steps forward for predictability : Consideration of methodological robustness, indexical and prosodic factors, and replication in the laboratory

There is now abundant evidence that phonetic forms are shaped by probabilistic effects reflecting predictability or informativity. We outline a number of challenges for such work, where theoretical claims are often based on small differences in acoustic measurements, or interpretations of small statistical effect sizes. We outline caveats about the methods and assumptions encountered in many studies of predictability effects, particularly regarding corpus-based approaches. We consider the wide range of factors that influence patterns of variability in phonetic forms, taking a broad perspective on what is meant by “the message” in order to show that predictability effects need to be considered alongside many others, including indexical and prosodic factors. We suggest a number of ways forward to extend our understanding of the form-predictability relationship.Full Tex

Sigma-lognormal modeling of speech

Human movement studies and analyses have been fundamental in many scientific domains, ranging from neuroscience to education, pattern recognition to robotics, health care to sports, and beyond. Previous speech motor models were proposed to understand how speech movement is produced and how the resulting speech varies when some parameters are changed. However, the inverse approach, in which the muscular response parameters and the subject’s age are derived from real continuous speech, is not possible with such models. Instead, in the handwriting field, the kinematic theory of rapid human movements and its associated Sigma-lognormal model have been applied successfully to obtain the muscular response parameters. This work presents a speech kinematics-based model that can be used to study, analyze, and reconstruct complex speech kinematics in a simplified manner. A method based on the kinematic theory of rapid human movements and its associated Sigma-lognormal model are applied to describe and to parameterize the asymptotic impulse response of the neuromuscular networks involved in speech as a response to a neuromotor command. The method used to carry out transformations from formants to a movement observation is also presented. Experiments carried out with the (English) VTR-TIMIT database and the (German) Saarbrucken Voice Database, including people of different ages, with and without laryngeal pathologies, corroborate the link between the extracted parameters and aging, on the one hand, and the proportion between the first and second formants required in applying the kinematic theory of rapid human movements, on the other. The results should drive innovative developments in the modeling and understanding of speech kinematics

Application of continuous state Hidden Markov Models to a classical problem in speech recognition

This paper describes an optimal algorithm using continuous state Hidden Markov Models for solving the HMS decoding problem, which is the problem of recov-ering an underlying sequence of phonetic units from measurements of smoothly varying acoustic features, thus inverting the speech generation process described by Holmes, Mattingly and Shearme in a well known paper (Speech synthesis by rule, Language and Speech 7 (1964))

Making accurate formant measurements: an empirical investigation of the influence of the measurement tool, analysis settings and speaker on formant measurements

The aim of this thesis is to provide guidance and information that will assist forensic speech scientists, and phoneticians generally, in making more accurate formant measurements, using commonly available speech analysis tools. Formant measurements are an important speech feature that are often examined in forensic casework, and are used widely in many other areas within the field of phonetics. However, the performance of software currently used by analysts has not been subject to detailed investigation. This thesis reports on a series of experiments that examine the influence that the analysis tools, analysis settings and speakers have on formant measurements. The influence of these three factors was assessed by examining formant measurement errors and their behaviour. This was done using both synthetic and real speech. The synthetic speech was generated with known formant values so that the measurement errors could be calculated precisely. To investigate the influence of different speakers on measurement performance, synthetic speakers were created with different third formant structures and with different glottal source signals. These speakers’ synthetic vowels were analysed using Praat’s normal formant measuring tool across a range of LPC orders. The real speech was from a subset of 186 speakers from the TIMIT corpus. The measurements from these speakers were compared with a set of hand-corrected reference formant values to establish the performance of four measurement tools across a range of analysis parameters and measurement strategies. The analysis of the measurement errors explored the relationships between the analysis tools, the analysis parameters and the speakers, and also examined how the errors varied over the vowel space. LPC order was found to have the greatest influence on the magnitude of the errors and their overall behaviour was closely associated with the underlying measurement process used by the tools. The performance of the formant trackers tended to be better than the simple Praat measuring tool, and allowing the LPC order to vary across tokens improved the performance for all tools. The performance was found to differ across speakers, and for each real speaker, the best performance was obtained when the measurements were made with a range of LPC orders, rather than being restricted to just one. The most significant guidance that arises from the results is that analysts should have an understanding of the basis of LPC analysis and know how it is applied to obtain formant measurements in the software that they use. They should also understand the influence of LPC order and the other analysis parameters concerning formant tracking. This will enable them to select the most appropriate settings and avoid making unreliable measurements