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Dynamic Speech Models - Theory, Algorithms, and Applications (Paperback)
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Dynamic Speech Models - Theory, Algorithms, and Applications (Paperback)
Series: Synthesis Lectures on Speech and Audio Processing
Expected to ship within 10 - 15 working days
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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
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