Speech Recognition Algorithms Using Weighted Finite-State Transducers (Synthesis Lectures on Speech and Audio Processing)

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Speech Recognition Algorithms Using Weighted Finite-State Transducers (Synthesis Lectures on Speech and Audio Processing)

In the field of speech recognition, weighted finite-state transducers (WFSTs) have emerged as a powerful tool for building efficient and accurate speech recognition systems. These transducers allow for the representation of speech recognition algorithms in a compact and flexible manner, making them ideal for handling the complex and variable nature of human speech.

In this comprehensive guide, the authors provide a detailed overview of the theory and implementation of WFST-based speech recognition algorithms. They cover the basics of WFSTs, including the definition of transducers, composition operations, and optimization techniques. The book also explores advanced topics such as discriminative training, language modeling, and acoustic modeling using WFSTs.

Whether you are a researcher, student, or practitioner in the field of speech and audio processing, this book is a valuable resource for understanding and implementing speech recognition algorithms using WFSTs. With its clear explanations, practical examples, and insightful discussions, Speech Recognition Algorithms Using Weighted Finite-State Transducers is a must-read for anyone interested in the latest advancements in speech recognition technology.
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