Research On Spoken Language Processing

Research on Spoken Language Processing

Spoken Language Processing

This book tackles the complexities of spontaneous human dialogues, exploring the challenges of unscripted conversations with their interruptions, overlaps, and disfluencies for conversational AI. It provides a comprehensive exploration of the differences between spontaneous and prescriptive languages, examining the impact of these differences on machine learning models. The author examines the technical aspects of processing spontaneous speech, including automatic speech recognition and transcript engineering, discussing the design and development of AI systems capable of handling the nuances of spontaneous dialogues. Written for researchers in natural language processing and students interested in AI and machine learning applications for spontaneous human communication, this book serves as a guide for understanding the latest advancements in the field and developing more robust and effective Conversational AI systems.

Spoken Language Processing

Spoken Language Processing draws on the latest advances and techniques from multiple fields: computer science, electrical engineering, acoustics, linguistics, mathematics, psychology, and beyond. Starting with the fundamentals, it presents all this and more: -Essential background on speech production and perception, probability and information theory, and pattern recognition -Extracting information from the speech signal: useful representations and practical compression solutions -Modern speech recognition techniques: hidden Markov models, acoustic and language modeling, improving resistance to environmental noises, search algorithms, and large vocabulary speech recognition -Text-to-speech: analyzing documents, pitch and duration controls; trainable synthesis, and more -Spoken language understanding: dialog ma.