Automatic Speech and Speaker Recognition advanced topics /
- Boston Kluwer academic publishers 1996.
- 517p
An Overview of Automatic Speech Recognition (Page-1), An Overview of Speaker Recognition Technology (Page-31), Maximum Mutual Information Estimation of Hidden Markov Models(Page-83), Statistical and Discriminative Methods for Speech Recognition (Page-109), Context Dependent Vector Quantization for Speech Recognition (Page-133), Hidden Markov Network for Precise Acoustic Modeling (Page-159), From HMMS To Segment Models : Stochastic Modeling for CSR(Page-211), The Use of Recurrent Networks in Continuous Speech Recognition (Page-233), Hybrid Connections Models for Continuous Speech Recognition (Page-285), World Spotting Extracting Partial Information from Continuous Utterances (Page-303), Spectral Dynamic for Speech Recognition under Adverse Conditions (Page-331), Single Processing for Robust Speech Recognition (Page-357), Dynamic Programming Search: From Digit Strings to Large Vocabulary World Graphs (Page-385), Fast Matching Techniques (Page-413), Multiple Pass Search Vocabulary (Page-429), Issues in Practical Large Vocabulary Isolated World Recognition : The IBM Isolated World Recognition The IBM Tagore Systems (Page-457), From Sphinx –II to Whisper Making Speech Recognition Usable (Page-481).