Dynamic Speech Models

"This book provides the scientific background, mathematical theory, computational framework, algorithmic development, and technological requirements for dynamic speech modeling. It focuses on two select applications."--BOOK JACKET.

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.

"Proceedings of the NATO Advanced Study Institute on Dynamics of Speech Production and Perception, Il Ciocco (Lucca), Italy, 23 June -6 July 2006"--T.p. verso.

Advances in Non-Linear Modeling for Speech Processing includes advanced topics in non-linear estimation and modeling techniques along with their applications to speaker recognition. Non-linear aeroacoustic modeling approach is used to estimate the important fine-structure speech events, which are not revealed by the short time Fourier transform (STFT). This aeroacostic modeling approach provides the impetus for the high resolution Teager energy operator (TEO). This operator is characterized by a time resolution that can track rapid signal energy changes within a glottal cycle. The cepstral features like linear prediction cepstral coefficients (LPCC) and mel frequency cepstral coefficients (MFCC) are computed from the magnitude spectrum of the speech frame and the phase spectra is neglected. To overcome the problem of neglecting the phase spectra, the speech production system can be represented as an amplitude modulation-frequency modulation (AM-FM) model. To demodulate the speech signal, to estimation the amplitude envelope and instantaneous frequency components, the energy separation algorithm (ESA) and the Hilbert transform demodulation (HTD) algorithm are discussed. Different features derived using above non-linear modeling techniques are used to develop a speaker identification system. Finally, it is shown that, the fusion of speech production and speech perception mechanisms can lead to a robust feature set.

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.

With a growing need for understanding the process involved in producing and perceiving spoken language, this timely publication answers these questions in an accessible reference. Containing material resulting from many years’ teaching and research, Speech Synthesis provides a complete account of the theory of speech. By bringing together the common goals and methods of speech synthesis into a single resource, the book will lead the way towards a comprehensive view of the process involved in human speech. The book includes applications in speech technology and speech synthesis. It is ideal for intermediate students of linguistics and phonetics who wish to proceed further, as well as researchers and engineers in telecommunications working in speech technology and speech synthesis who need a comprehensive overview of the field and who wish to gain an understanding of the objectives and achievements of the study of speech production and perception.

Speech sound production is one of the most complex human activities: it is also one of the least well understood. This is perhaps not altogether surprising as many of the complex neurological and physiological processes involved in the generation and execution of a speech utterance remain relatively inaccessible to direct investigation, and must be inferred from careful scrutiny of the output of the system -from details of the movements of the speech organs themselves and the acoustic consequences of such movements. Such investigation of the speech output have received considerable impetus during the last decade from major technological advancements in computer science and biological transducing, making it possible now to obtain large quantities of quantative data on many aspects of speech articulation and acoustics relatively easily. Keeping pace with these advancements in laboratory techniques have been developments in theoretical modelling of the speech production process. There are now a wide variety of different models available, reflecting the different disciplines involved -linguistics, speech science and technology, engineering and acoustics. The time seems ripe to attempt a synthesis of these different models and theories and thus provide a common forum for discussion of the complex problem of speech production. Such an activity would seem particularly timely also for those colleagues in speech technology seeking better, more accurate phonetic models as components in their speech synthesis and automatic speech recognition systems.