| Techniques to Achieve an Accurate Real-Time Large-Vocabulary Speech Recognition System |
1994 |
7 pages |
| Authors:
Hy Murveit; Peter Monaco; Vassilios Digalakis; John Butzberger; SRI INTERNATIONAL MENLO PARK CA
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 | In addressing the problem of achieving high-accuracy real-time speech recognition systems, we focus on recognizing speech from ARPA's 20,000-word Wall Street Journal (WSJ) task, using current UNIX workstations. We have found that our standard approach-using a narrow beam width in a viterbi search for simple discrete-density hidden Markov models (HMMs)-works in real time with only very low accuracy. Our most accurate algorithms recognize speech many times slower than real time. ... |
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| High-Accuracy Large-Vocabulary Speech Recognition Using Mixture Tying and Consistency Modeling |
1994 |
7 pages |
| Authors:
Vassilios Digalakis; Hy Murveit; SRI INTERNATIONAL MENLO PARK CA
|
| Improved acoustic modeling can significantly decrease the error rate in large-vocabulary speech recognition. Our approach to the problem is twofold. We first propose a scheme that optimizes the degree of mixture tying for a given amount of training data and computational resources. Experimental results on the Wall Street Journal (WSJ) Corpus show that this new form of output distribution achieves a 25% reduction in error rate over typical tied- mixture ... |
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| Progressive-Search Algorithms for Large-Vocabulary Speech Recognition |
1993 |
5 pages |
| Authors:
Hy Murveit; John Butzberger; Vassilios Digalakis; Mitch Weintraub; SRI INTERNATIONAL MENLO PARK CA
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| The authors describe a technique they call "Progressive Search," which is useful for developing and implementing speech recognition systems with high computational requirements. The scheme iteratively uses more and more complex recognition schemes, where each iteration constrains the search space of the next. An algorithm, the "Forward-Backward Word-Life Algorithm," is described. It can generate a word lattice in a progressive search that would be used as a language model embedded ... |
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| Spontaneous Speech Effects in Large Vocabulary Speech Recognition Applications |
FEB 1992 |
6 pages |
| Authors:
John Butzberger; Hy Murveit; Elizabeth Shriberg; Patti Price; SRI INTERNATIONAL MENLO PARK CA
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| We describe three analyses on the effects of spontaneous speech on continuous speech recognition performance. We have found that: (1) spontaneous speech effects significantly degrade recognition performance, (2) fluent spontaneous speech yields word accuracies equivalent to read speech, and (3) using spontaneous speech training data can significantly improve performance for recognizing spontaneous speech. We conclude that word accuracy can be improved by explicitly modeling spontaneous effects in the recognizer, and ... |
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| Performance of SRI's Decipher Speech Recognition System on DARPA's CSR Task |
1992 |
6 pages |
| Authors:
Hy Murveit; John Butzberger; Mitch Weintraub; SRI INTERNATIONAL MENLO PARK CA
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| SRI has ported its DECIPHER(trademark) speech recognition system from DARPA's ATIS domain to DARPA's CSR domain (read and spontaneous Wall Street Journal speech). This paper describes what needed to be done to port DECIPHER(trademark), and reports experiments performed with the CSR task. The system was evaluated on the speaker-independent (SI) portion of DARPA's February 1992 "Dry-Run" WSJ0 test and achieved 17.1% word error without verbalized punctuation (NVP) and 16.6% error ... |
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