Large vocabulary continuous speech recognition of Wall Street Journal data
| Autor: | Robert Roth, James Baker, Janet Baker, Larry Gillick, Melvyn Hunt, Yoshiko Ito, Stephen Lowe, Jeremy Orloff, Barbara Peskin, Francesco Scottone |
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| Rok vydání: | 1993 |
| Předmět: |
Vocabulary
Context model Signal processing Computer science business.industry Speech recognition media_common.quotation_subject computer.software_genre Reduction (complexity) Transformation (function) Artificial intelligence Hidden Markov model business computer Natural language processing media_common |
| Zdroj: | ICASSP (2) |
| DOI: | 10.1109/icassp.1993.319391 |
| Popis: | The authors report on the progress that has been made at Dragon Systems in speaker-independent large-vocabulary speech recognition using speech from DARPA's Wall Street Journal corpus. First they present an overview of the recognition and training algorithms. Then, they describe experiments involving two improvements to these algorithms, moving to higher-dimensional streams and using an IMELDA transformation. They also present some results showing the reduction in error rates. > |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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