Intonation modelling using a muscle model and perceptually weighted matching pursuit

We propose a physiologically based intonation model using perceptual relevance. Motivated by speech synthesis from a speech-to-speech translation (S2ST) point of view, we aim at a language independent way of modelling intonation. The model presented in this paper can be seen as a generalisation of the command response (CR) model, albeit with the same modelling power. It is an additive model which decomposes intonation contours into a sum of critically damped system impulse responses. To decompose the intonation contour, we use a weighted correlation based atom decomposition algorithm (WCAD) built around a matching pursuit framework. The algorithm allows for an arbitrary precision to be reached using an iterative procedure that adds more elementary atoms to the model. Experiments are presented demonstrating that this generalised CR (GCR) model is able to model intonation as would be expected. Experiments also show that the model produces a similar number of parameters or elements as the CR model. We conclude that the GCR model is appropriate as an engineering solution for modelling prosody, and hope that it is a contribution to a deeper scientific understanding of the neurobiological process of intonation

Auditory communication in domestic dogs: vocal signalling in the extended social environment of a companion animal

Domestic dogs produce a range of vocalisations, including barks, growls, and whimpers, which are shared with other canid species. The source–filter model of vocal production can be used as a theoretical and applied framework to explain how and why the acoustic properties of some vocalisations are constrained by physical characteristics of the caller, whereas others are more dynamic, influenced by transient states such as arousal or motivation. This chapter thus reviews how and why particular call types are produced to transmit specific types of information, and how such information may be perceived by receivers. As domestication is thought to have caused a divergence in the vocal behaviour of dogs as compared to the ancestral wolf, evidence of both dog–human and human–dog communication is considered. Overall, it is clear that domestic dogs have the potential to acoustically broadcast a range of information, which is available to conspecific and human receivers. Moreover, dogs are highly attentive to human speech and are able to extract speaker identity, emotional state, and even some types of semantic information

Temporal integration in the perception of speech: Introduction

International audienceIn studies of speech perception, temporal integration refers to how chunks of information arriving at the ears at different times are linked together by the listener in mapping speech sounds onto meaning. Classical models focused on the perceptual grouping of acoustic cues contained in short stretches of time in the identification of phonetic segments. In recent years, however, a different view has emerged as speech perception has come to be studied within a broader context and from a multidisciplinary perspective. Thus, the relevance of non-local, long-domain cues to phonological contrasts has been demonstrated. The status of the phonetic segment as a basic perceptual unit has been debated. And the primacy of the auditory channel over the visual channel has been questioned. These issues have profound implications for how temporal integration is defined and accounted for

Temporal integration in the perception of speech: Introduction

International audienceIn studies of speech perception, temporal integration refers to how chunks of information arriving at the ears at different times are linked together by the listener in mapping speech sounds onto meaning. Classical models focused on the perceptual grouping of acoustic cues contained in short stretches of time in the identification of phonetic segments. In recent years, however, a different view has emerged as speech perception has come to be studied within a broader context and from a multidisciplinary perspective. Thus, the relevance of non-local, long-domain cues to phonological contrasts has been demonstrated. The status of the phonetic segment as a basic perceptual unit has been debated. And the primacy of the auditory channel over the visual channel has been questioned. These issues have profound implications for how temporal integration is defined and accounted for

Doctor of Philosophy

dissertationHearing aids suffer from the problem of acoustic feedback that limits the gain provided by hearing aids. Moreover, the output sound quality of hearing aids may be compromised in the presence of background acoustic noise. Digital hearing aids use advanced signal processing to reduce acoustic feedback and background noise to improve the output sound quality. However, it is known that the output sound quality of digital hearing aids deteriorates as the hearing aid gain is increased. Furthermore, popular subband or transform domain digital signal processing in modern hearing aids introduces analysis-synthesis delays in the forward path. Long forward-path delays are not desirable because the processed sound combines with the unprocessed sound that arrives at the cochlea through the vent and changes the sound quality. In this dissertation, we employ a variable, frequency-dependent gain function that is lower at frequencies of the incoming signal where the information is perceptually insignificant. In addition, the method of this dissertation automatically identifies and suppresses residual acoustical feedback components at frequencies that have the potential to drive the system to instability. The suppressed frequency components are monitored and the suppression is removed when such frequencies no longer pose a threat to drive the hearing aid system into instability. Together, the method of this dissertation provides more stable gain over traditional methods by reducing acoustical coupling between the microphone and the loudspeaker of a hearing aid. In addition, the method of this dissertation performs necessary hearing aid signal processing with low-delay characteristics. The central idea for the low-delay hearing aid signal processing is a spectral gain shaping method (SGSM) that employs parallel parametric equalization (EQ) filters. Parameters of the parametric EQ filters and associated gain values are selected using a least-squares approach to obtain the desired spectral response. Finally, the method of this dissertation switches to a least-squares adaptation scheme with linear complexity at the onset of howling. The method adapts to the altered feedback path quickly and allows the patient to not lose perceivable information. The complexity of the least-squares estimate is reduced by reformulating the least-squares estimate into a Toeplitz system and solving it with a direct Toeplitz solver. The increase in stable gain over traditional methods and the output sound quality were evaluated with psychoacoustic experiments on normal-hearing listeners with speech and music signals. The results indicate that the method of this dissertation provides 8 to 12 dB more hearing aid gain than feedback cancelers with traditional fixed gain functions. Furthermore, experimental results obtained with real world hearing aid gain profiles indicate that the method of this dissertation provides less distortion in the output sound quality than classical feedback cancelers, enabling the use of more comfortable style hearing aids for patients with moderate to profound hearing loss. Extensive MATLAB simulations and subjective evaluations of the results indicate that the method of this dissertation exhibits much smaller forward-path delays with superior howling suppression capability

Intonation Modelling for Speech Synthesis and Emphasis Preservation

Speech-to-speech translation is a framework which recognises speech in an input language, translates it to a target language and synthesises speech in this target language. In such a system, variations in the speech signal which are inherent to natural human speech are lost, as the information goes through the different building blocks of the translation process. The work presented in this thesis addresses aspects of speech synthesis which are lost in traditional speech-to-speech translation approaches. The main research axis of this thesis is the study of prosody for speech synthesis and emphasis preservation. A first investigation of regional accents of spoken French is carried out to understand the sensitivity of native listeners with respect to accented speech synthesis. Listening tests show that standard adaptation methods for speech synthesis are not sufficient for listeners to perceive accentedness. On the other hand, combining adaptation with original prosody allows perception of accents. Addressing the need of a more suitable prosody model, a physiologically plausible intonation model is proposed. Inspired by the command-response model, it has basic components, which can be related to muscle responses to nerve impulses. These components are assumed to be a representation of muscle control of the vocal folds. A motivation for such a model is its theoretical language independence, based on the fact that humans share the same vocal apparatus. An automatic parameter extraction method which integrates a perceptually relevant measure is proposed with the model. This approach is evaluated and compared with the standard command-response model. Two corpora including sentences with emphasised words are presented, in the context of the SIWIS project. The first is a multilingual corpus with speech from multiple speaker; the second is a high quality speech synthesis oriented corpus from a professional speaker. Two broad uses of the model are evaluated. The first shows that it is difficult to predict model parameters; however the second shows that parameters can be transferred in the context of emphasis synthesis. A relation between model parameters and linguistic features such as stress and accent is demonstrated. Similar observations are made between the parameters and emphasis. Following, we investigate the extraction of atoms in emphasised speech and their transfer in neutral speech, which turns out to elicit emphasis perception. Using clustering methods, this is extended to the emphasis of other words, using linguistic context. This approach is validated by listening tests, in the case of English

Automatic voice disorder recognition using acoustic amplitude modulation features

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 114-117).An automatic dysphonia recognition system is designed that exploits amplitude modulations (AM) in voice using biologically-inspired models. This system recognizes general dysphonia and four subclasses: hyperfunction, A-P squeezing, paralysis, and vocal fold lesions. The models developed represent processing in the auditory system at the level of the cochlea, auditory nerve, and inferior colliculus. Recognition experiments using dysphonic sentence data obtained from the Kay Elemetrics Disordered Voice Database suggest that our system provides complementary information to state-of-the-art mel-cepstral features. A model for analyzing AM in dysphonic speech is also developed from a traditional communications engineering perspective. Through a case study of seven disordered voices, we show that different AM patterns occur in different frequency bands. This perspective challenges current dysphonia analysis methods that analyze AM in the time-domain signal.by Nicolas Malyska.S.M

Parameterization of a computational physical model for glottal flow using inverse filtering and high-speed videoendoscopy

High-speed videoendoscopy, glottal inverse filtering, and physical modeling can be used to obtain complementary information about speech production. In this study, the three methodologies are combined to pursue a better understanding of the relationship between the glottal air flow and glottal area. Simultaneously acquired high-speed video and glottal inverse filtering data from three male and three female speakers were used. Significant correlations were found between the quasi-open and quasi-speed quotients of the glottal area (extracted from the high-speed videos) and glottal flow (estimated using glottal inverse filtering), but only the quasi-open quotient relationship could be represented as a linear model. A simple physical glottal flow model with three different glottal geometries was optimized to match the data. The results indicate that glottal flow skewing can be modeled using an inertial vocal/subglottal tract load and that estimated inertia within the glottis is sensitive to the quality of the data. Parameter optimisation also appears to favour combining the simplest glottal geometry with viscous losses and the more complex glottal geometries with entrance/exit effects in the glottis.Peer reviewe