Provides a theoretically sound, technically accurate, and complete description of the basic knowledge and ideas that constitute a modern system for speech recognition by machine. Covers production, perc...

Buy Now From Amazon

Provides a theoretically sound, technically accurate, and complete description of the basic knowledge and ideas that constitute a modern system for speech recognition by machine. Covers production, perception, and acoustic-phonetic characterization of the speech signal; signal processing and analysis methods for speech recognition; pattern comparison techniques; speech recognition system design and implementation; theory and implementation of hidden Markov models; speech recognition based on connected word models; large vocabulary continuous speech recognition; and task- oriented application of automatic speech recognition. For practicing engineers, scientists, linguists, and programmers interested in speech recognition.



Similar Products

Automatic Speech Recognition: A Deep Learning Approach (Signals and Communication Technology)Deep Learning (Adaptive Computation and Machine Learning series)Statistical Methods for Speech Recognition (Language, Speech, and Communication)Digital Processing of Speech SignalsPattern Recognition and Machine Learning (Information Science and Statistics)Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent SystemsReinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)Make Your Own Neural Network