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Speech: A dynamic process takes readers on a rigorous exploratory journey to expose them to the inherently dynamic nature of speech. The book addresses an intriguing question: Based only on physical principles alone, can the exploitation of a simple acoustic tube evolve into an optimal speech production system comparable to the one we possess? In the work presented, the tube is deformed step by step with the sole criterion of expending minimum effort to obtain maximum acoustic variations. At the end of this process, the tube is found divided into distinctive regions and an acoustic space emerges capable of generating speech sounds. Attaching this tube to a model, an inherently dynamic and efficient system is created. In the resulting system, optimal primitive trajectories are seen to naturally exist in the acoustic space and the regions defined in the tube correspond to the main places of articulation for oral vowels and plosive consonants. All this implies that these speech sounds are inherent properties of not only the modeled acoustic tube but also of the human speech production system. This book stands as a valuable resource for accomplished and aspiring speech scientists as well as for other interested persons in search for an introduction to speech acoustics that takes an unconventional path.
Speech dynamics refer to the temporal characteristics in all stages of the human speech communication process. This speech “chain” starts with the formation of a linguistic message in a speaker's brain and ends with the arrival of the message in a listener's brain. Given the intricacy of the dynamic speech process and its fundamental importance in human communication, this monograph is intended to provide a comprehensive material on mathematical models of speech dynamics and to address the following issues: How do we make sense of the complex speech process in terms of its functional role of speech communication? How do we quantify the special role of speech timing? How do the dynamics relate to the variability of speech that has often been said to seriously hamper automatic speech recognition? How do we put the dynamic process of speech into a quantitative form to enable detailed analyses? And finally, how can we incorporate the knowledge of speech dynamics into computerized speech analysis and recognition algorithms? The answers to all these questions require building and applying computational models for the dynamic speech process. What are the compelling reasons for carrying out dynamic speech modeling? We provide the answer in two related aspects. First, scientific inquiry into the human speech code has been relentlessly pursued for several decades. As an essential carrier of human intelligence and knowledge, speech is the most natural form of human communication. Embedded in the speech code are linguistic (as well as para-linguistic) messages, which are conveyed through four levels of the speech chain. Underlying the robust encoding and transmission of the linguistic messages are the speech dynamics at all the four levels. Mathematical modeling of speech dynamics provides an effective tool in the scientific methods of studying the speech chain. Such scientific studies help understand why humans speak as they do and how humans exploit redundancy and variability by way of multitiered dynamic processes to enhance the efficiency and effectiveness of human speech communication. Second, advancement of human language technology, especially that in automatic recognition of natural-style human speech is also expected to benefit from comprehensive computational modeling of speech dynamics. The limitations of current speech recognition technology are serious and are well known. A commonly acknowledged and frequently discussed weakness of the statistical model underlying current speech recognition technology is the lack of adequate dynamic modeling schemes to provide correlation structure across the temporal speech observation sequence. Unfortunately, due to a variety of reasons, the majority of current research activities in this area favor only incremental modifications and improvements to the existing HMM-based state-of-the-art. For example, while the dynamic and correlation modeling is known to be an important topic, most of the systems nevertheless employ only an ultra-weak form of speech dynamics; e.g., differential or delta parameters. Strong-form dynamic speech modeling, which is the focus of this monograph, may serve as an ultimate solution to this problem. After the introduction chapter, the main body of this monograph consists of four chapters. They cover various aspects of theory, algorithms, and applications of dynamic speech models, and provide a comprehensive survey of the research work in this area spanning over past 20~years. This monograph is intended as advanced materials of speech and signal processing for graudate-level teaching, for professionals and engineering practioners, as well as for seasoned researchers and engineers specialized in speech processing
That speech is a dynamic process strikes as a tautology: whether from the standpoint of the talker, the listener, or the engineer, speech is an action, a sound, or a signal continuously changing in time. This book presents a collection of papers which looks at speech as a dynamic process and highlights its particularities.
The idea that speech is a dynamic process is a tautology: whether from the standpoint of the talker, the listener, or the engineer, speech is an action, a sound, or a signal continuously changing in time. Yet, because phonetics and speech science are offspring of classical phonology, speech has been viewed as a sequence of discrete events-positions of the articulatory apparatus, waveform segments, and phonemes. Although this perspective has been mockingly referred to as "beads on a string", from the time of Henry Sweet's 19th century treatise almost up to our days specialists of speech science and speech technology have continued to conceptualize the speech signal as a sequence of static states interleaved with transitional elements reflecting the quasi-continuous nature of vocal production. This book, a collection of papers of which each looks at speech as a dynamic process and highlights one of its particularities, is dedicated to the memory of Ludmilla Andreevna Chistovich. At the outset, it was planned to be a Chistovich festschrift but, sadly, she passed away a few months before the book went to press. The 24 chapters of this volume testify to the enormous influence that she and her colleagues have had over the four decades since the publication of their 1965 monograph.
Speech dynamics refer to the temporal characteristics in all stages of the human speech communication process. This speech “chain” starts with the formation of a linguistic message in a speaker's brain and ends with the arrival of the message in a listener's brain. Given the intricacy of the dynamic speech process and its fundamental importance in human communication, this monograph is intended to provide a comprehensive material on mathematical models of speech dynamics and to address the following issues: How do we make sense of the complex speech process in terms of its functional role of speech communication? How do we quantify the special role of speech timing? How do the dynamics relate to the variability of speech that has often been said to seriously hamper automatic speech recognition? How do we put the dynamic process of speech into a quantitative form to enable detailed analyses? And finally, how can we incorporate the knowledge of speech dynamics into computerized speech analysis and recognition algorithms? The answers to all these questions require building and applying computational models for the dynamic speech process. What are the compelling reasons for carrying out dynamic speech modeling? We provide the answer in two related aspects. First, scientific inquiry into the human speech code has been relentlessly pursued for several decades. As an essential carrier of human intelligence and knowledge, speech is the most natural form of human communication. Embedded in the speech code are linguistic (as well as para-linguistic) messages, which are conveyed through four levels of the speech chain. Underlying the robust encoding and transmission of the linguistic messages are the speech dynamics at all the four levels. Mathematical modeling of speech dynamics provides an effective tool in the scientific methods of studying the speech chain. Such scientific studies help understand why humans speak as they do and how humans exploit redundancy and variability by way of multitiered dynamic processes to enhance the efficiency and effectiveness of human speech communication. Second, advancement of human language technology, especially that in automatic recognition of natural-style human speech is also expected to benefit from comprehensive computational modeling of speech dynamics. The limitations of current speech recognition technology are serious and are well known. A commonly acknowledged and frequently discussed weakness of the statistical model underlying current speech recognition technology is the lack of adequate dynamic modeling schemes to provide correlation structure across the temporal speech observation sequence. Unfortunately, due to a variety of reasons, the majority of current research activities in this area favor only incremental modifications and improvements to the existing HMM-based state-of-the-art. For example, while the dynamic and correlation modeling is known to be an important topic, most of the systems nevertheless employ only an ultra-weak form of speech dynamics; e.g., differential or delta parameters. Strong-form dynamic speech modeling, which is the focus of this monograph, may serve as an ultimate solution to this problem. After the introduction chapter, the main body of this monograph consists of four chapters. They cover various aspects of theory, algorithms, and applications of dynamic speech models, and provide a comprehensive survey of the research work in this area spanning over past 20~years. This monograph is intended as advanced materials of speech and signal processing for graudate-level teaching, for professionals and engineering practioners, as well as for seasoned researchers and engineers specialized in speech processing
Based on years of instruction and field expertise, this volume offers the necessary tools to understand all scientific, computational, and technological aspects of speech processing. The book emphasizes mathematical abstraction, the dynamics of the speech process, and the engineering optimization practices that promote effective problem solving in this area of research and covers many years of the authors' personal research on speech processing. Speech Processing helps build valuable analytical skills to help meet future challenges in scientific and technological advances in the field and considers the complex transition from human speech processing to computer speech processing.
While there is general acknowledgement that communication is a process rather than a condition, there has been little systematic examination of dynamic processes within communication studies. This volume examines these processes within the communications field as a whole, from interpersonal to mass communication, and thereby brings to light many largely unexplored connections. The first part focuses on the methodological and theoretical significance of communication events or states which vary regularly, or in some distinct pattern, over time. The second section is a compilation of current theories and research based on the ideas of cyclic and dynamic patterns which occur in diverse communication settings.
This monograph arose from a conference on the Production of Speech held at the University of Texas at Austin on April 28-30, 1981. It was sponsored by the Center for Cognitive Science, the College of Liberal Arts, and the Linguistics and Psychology Departments. The conference was the second in a series of conferences on human experimental psychology: the first, held to commemorate the 50th anniversary of the founding of the Psychology Department, resulted in publication of the monograph Neural Mechanisms in Behavior, D. McFadden (Ed.), Springer-Verlag, 1980. The choice of the particular topic of the second conference was motivated by the belief that the state of knowledge of speech production had recently reached a critical mass, and that a good deal was to be gained from bringing together the foremost researchers in this field. The benefits were the opportunity for the participants to compare notes on their common problems, the publication of a monograph giving a comprehensive state-of-the-art picture of this research area, and the provision of enormous intellectual stimulus for local students of this topic.
Understanding Language: An Information-Processing Analysis of Speech Perception, Reading, and Psycholinguistics focuses on the progress of approaches, principles, and practices involved in speech perception, reading, and psycholinguistics. The selection first offers information on language and information processing, articulatory and acoustic characteristics of speech sounds, and acoustic features in speech perception. Discussions focus on vowel and consonant recognition, production of speech sounds, general acoustic properties and occurrence of speech sounds, vowel phonemes of English, and information, auditory, and visual information processing. The text then examines preperceptual images, processing time, and perceptual units in speech perception, theories of perception, and visual features, preperceptual storage, and processing time in reading. Topics include processing time, visual features, summary of information-processing analysis of speech perception, role of linguistic structure in model building, and preperceptual images and processing time. The manuscript takes a look at an analysis of psychological studies of grammar, word and phrase recognition in speech processing, and linguistic theory and information processing, including psychological function of certain transformation rules, psychological reality of constituent structure, and linguistics and psychology. The selection is a vital source of data for researchers interested in speech perception, reading, and psycholinguistics.
By upending traditional perspectives, this book gives a biologically-grounded understanding of how spoken language conveys meaning.