Abstract
The authors describe an experimental text-to-speech system that uses a syntactic parser and prosody rules to determine prosodic phrasing for synthesized speech. It is shown that many aspects of sentence analysis that are required for other parsing applications, e.g., machine translation and question answering, become unnecessary in parsing for text-to-speech. It is possible to generate natural-sounding prosodic phrasing by relying on information about syntactic category type, partial constituency, and length; information about clausal and verb phrase constituency, predicate-argument relations, and prepositional phrase attachment can be bypassed.
Original language | English |
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Title of host publication | Proc Annu AI Syst Gov Conf |
Editors | James H. Antonisse, John W. Benoit, Barry G. Silverman |
Pages | 188-194 |
Number of pages | 7 |
State | Published - 1 Dec 1989 |
Event | Proceedings of the Annual AI Systems in Government Conference - Washington, DC, USA Duration: 27 Mar 1989 → 31 Mar 1989 |
Other
Other | Proceedings of the Annual AI Systems in Government Conference |
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City | Washington, DC, USA |
Period | 27/03/89 → 31/03/89 |