Robust Estimation of Tone Break Indices from Speech Signal using Multi-Scale Analysis and their Applications

The aim of this study is to develop robust algorithm to automatically detect the Tone and Break Indices(ToBI) from the speech signal and explore their applications. iLAST was introduced to analyze the acoustic and prosodic features to detect the ToBI indices. Both expert and data driven rules were used to improve the robustness. The integration of multi-scale signal analysis with rule-based classification has helped in robustly identifying tones that can be used in applications, such as identifying Vowel triangle, emotions from speech etc. Empirical analyses using labeled dataset were performed to illustrate the utility of the proposed approach. Further analyses were conducted to identify the inefficiencies with the proposed approach and address those issues through co-analyses of prosodic features in identifying the major contributors to robust detection of ToBI. It was demonstrated that the proposed approach performs robustly and can be used for developing a wide variety of applications

Universal and language-specific processing : the case of prosody

A key question in the science of language is how speech processing can be influenced by both language-universal and language-specific mechanisms (Cutler, Klein, & Levinson, 2005). My graduate research aimed to address this question by adopting a crosslanguage approach to compare languages with different phonological systems. Of all components of linguistic structure, prosody is often considered to be one of the most language-specific dimensions of speech. This can have significant implications for our understanding of language use, because much of speech processing is specifically tailored to the structure and requirements of the native language. However, it is still unclear whether prosody may also play a universal role across languages, and very little comparative attempts have been made to explore this possibility. In this thesis, I examined both the production and perception of prosodic cues to prominence and phrasing in native speakers of English and Mandarin Chinese. In focus production, our research revealed that English and Mandarin speakers were alike in how they used prosody to encode prominence, but there were also systematic language-specific differences in the exact degree to which they enhanced the different prosodic cues (Chapter 2). This, however, was not the case in focus perception, where English and Mandarin listeners were alike in the degree to which they used prosody to predict upcoming prominence, even though the precise cues in the preceding prosody could differ (Chapter 3). Further experiments examining prosodic focus prediction in the speech of different talkers have demonstrated functional cue equivalence in prosodic focus detection (Chapter 4). Likewise, our experiments have also revealed both crosslanguage similarities and differences in the production and perception of juncture cues (Chapter 5). Overall, prosodic processing is the result of a complex but subtle interplay of universal and language-specific structure

Robust speech/non-speech detection based on LDAderived parameter and voicing parameter for speech recognition in noisy environments

Abstract Every speech recognition system contains a speech/non-speech detection stage. Detected speech sequences are only passed through the speech recognition stage later on. In a very noisy environment, the noise detection stage is generally responsible for most of the recognition errors. Indeed, many detected noisy periods can be recognized as a vocabulary word. This manuscript provides solutions to improve the performance of a speech/non-speech detection system in very noisy environment (for both stationary and short-time energetic noise), with an application to the France Télécom system. The improvement we propose are threefold. First, noise reduction is considered in order to reduce stationary noise effects on the speech detection system. Then, in order to decrease detections of noise characterized by brief duration and high energy, two new versions of the speech/non-speech detection stage are proposed. On the one hand, a linear discriminate analysis algorithm applied to the Mel frequency cepstrum coefficients is incorporated in the speech/nonspeech detection algorithm. On the other hand, the use of a voicing parameter is introduced in the speech/non-speech detection in order to reduce the probability of false noise detections

Methods in prosody

This book presents a collection of pioneering papers reflecting current methods in prosody research with a focus on Romance languages. The rapid expansion of the field of prosody research in the last decades has given rise to a proliferation of methods that has left little room for the critical assessment of these methods. The aim of this volume is to bridge this gap by embracing original contributions, in which experts in the field assess, reflect, and discuss different methods of data gathering and analysis. The book might thus be of interest to scholars and established researchers as well as to students and young academics who wish to explore the topic of prosody, an expanding and promising area of study

A model of sonority based on pitch intelligibility

Synopsis: Sonority is a central notion in phonetics and phonology and it is essential for generalizations related to syllabic organization. However, to date there is no clear consensus on the phonetic basis of sonority, neither in perception nor in production. The widely used Sonority Sequencing Principle (SSP) represents the speech signal as a sequence of discrete units, where phonological processes are modeled as symbol manipulating rules that lack a temporal dimension and are devoid of inherent links to perceptual, motoric or cognitive processes. The current work aims to change this by outlining a novel approach for the extraction of continuous entities from acoustic space in order to model dynamic aspects of phonological perception. It is used here to advance a functional understanding of sonority as a universal aspect of prosody that requires pitch-bearing syllables as the building blocks of speech. This book argues that sonority is best understood as a measurement of pitch intelligibility in perception, which is closely linked to periodic energy in acoustics. It presents a novel principle for sonority-based determinations of well-formedness – the Nucleus Attraction Principle (NAP). Two complementary NAP models independently account for symbolic and continuous representations and they mostly outperform SSP-based models, demonstrated here with experimental perception studies and with a corpus study of Modern Hebrew nouns. This work also includes a description of ProPer (Prosodic Analysis with Periodic Energy). The ProPer toolbox further exploits the proposal that periodic energy reflects sonority in order to cover major topics in prosodic research, such as prominence, intonation and speech rate. The book is finally concluded with brief discussions on selected topics: (i) the phonotactic division of labor with respect to /s/-stop clusters; (ii) the debate about the universality of sonority; and (iii) the fate of the classic phonetics–phonology dichotomy as it relates to continuity and dynamics in phonology