The BBN BYBLOS Continuous Speech Recognition System
نویسندگان
چکیده
In this paper we describe the algorithms used in the BBN BYBLOS Continuous Speech Recognition system. The BYBLOS system uses context-dependent hidden Markov models of phonemes to provide a robust model of phonetic coarticulation. We provide an update of the ongoing research aimed at improving the recognition accuracy. In the first experiment we confirm the large improvement in accuracy that can be derived by using spectral derivative parameters in the recognition. In particular, the word error rate is reduced by a factor of two. Currently the system achieves a word error rate of 2.9% when tested on the speaker-dependent part of the standard 1000-Word DARPA Resource Management Database using the Word-Pair grammar supplied with the database. When no grammar was used, the error rate is 15.3%. Finally, we present a method for smoothing the discrete densities on the states of the HMM, which is intended to alleviate the problem of insufficient training for detailed phonetic models.
منابع مشابه
The 2000 BBN Byblos LVCSR system
This paper describes the 2000 BBN Byblos Large Vocabulary Continuous Speech Recognition (LVCSR) system. We briefly outline the training and decoding procedures used in the system, and explain in detail the new features we have added to the system in the past year. These new features include multiple adaptation stages, parallel path rescoring, and a new word confidence system. Word error rate re...
متن کاملThe BBN Byblos 1997 large vocabulary conversational speech recognition system
This paper presents the 1997 BBN Byblos Large Vocabulary Speech Recognition (LVCSR) system. We give an outline of the algorithms and procedures used to train the system, describe the recognizer configuration and present the major technological innovations that lead to performance improvements. The major testbed we present our results for is the Switchboard Corpus, where current word error rates...
متن کاملLanguage-independent OCR using a continuous speech recognition system
In this paper we show how continuous speech recognition methods can be used for character recognition, resulting in a technology that is language independent and does not require presegmentation of the data at the character and word levels. In multi-font experiments on the ARPA Arabic OCR Corpus an average character error rate of 1.9% is obtained using the BBN BYBLOS Continuous Speech Recogniti...
متن کاملThe BBN Byblos 2000 conversational Mandarin LVCSR system
This paper describes the year 2000 BBN Byblos Mandarin large vocabulary conversational speech recognition (LVCSR) system, the winning (and only) Mandarin system from the Spring 2000 Hub-5 evaluation sponsored by NIST. We first outline the training and decoding procedures used in the system, and describe the performance of the system used in the evaluation. We then describe the effect of several...
متن کاملSpeaker Adaptation from Limited Training in the BBN BYBLOS Speech Recognition System
The BBN BYBLOS continuous speech recognition system has been used to develop a method of speaker adaptation from limited training. The key step in the method is the estimation of a probabilistic spectral mapping between a prototype speaker, for whom there exists a well-trained speaker-dependent hidden Markov model (HMM), and a target speaker for whom there is only a small amount of training spe...
متن کامل