Automatic Speech Recognition and UnderstandingIEEE, 2001 - Automatic speech recognition |
Contents
Keynotes | 1 |
Brancusi Neoplasticism and the Art of Designing SpeechRecognition Application | 9 |
Adaptive Training for Robust | 15 |
Copyright | |
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acoustic models adaptive training AIBO algorithm alignment application approach arg max audio automatic Automatic Speech Recognition baseline beam search bigram cepstral cepstrum classifier clustering coefficients components computed context database decision tree decoding dialog digit domain Eigenvoice estimate evaluation example experiments extracted feature extraction feature vector Figure filter finite-state frame frequency Gaussian grammar Hidden Markov Models hypotheses ICASSP IEEE improvement input interface iteration language model large vocabulary lexical lexicon likelihood method MFCC microphone MLLR N-best n-gram node noise noisy normalization optimal output paper parameters performance phoneme probability Proc pronunciation proposed pruning query recognition accuracy recognizer reduce retrieval robust score segmentation selected semantic sentence sequence shows speaker spectral speech recognition system speech signal string Table target task techniques test set tion training corpus training data training set transcription transducer transform tree utterances VoiceXML word error rate