Hardware for hidden Markov-model-based, large-vocabulary real-time speech recognition
| Autor: | M. Weintraub, H. Murveit, J. Mankoski, G. Chen |
|---|---|
| Rok vydání: | 1990 |
| Předmět: |
Vocabulary
business.industry Computer science media_common.quotation_subject Bigram Speech recognition Speech technology computer.software_genre Trigram Artificial intelligence Architecture business Hidden Markov model computer Natural language processing Computer hardware media_common Spoken language |
| Zdroj: | HLT |
| DOI: | 10.3115/116580.116611 |
| Popis: | SRI and U.C. Berkeley have begun a cooperative effort to develop a new architecture for real-time implementation of spoken language systems (SLS). Our goal is to develop fast speech recognition algorithms, and supporting hardware capable of recognizing continuous speech from a bigram- or trigram-based 20,000-word vocabulary or a 1,000- to 5,000-word SLS. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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