Knowledge Base and Its Environment for Continuous Speech Recongnition
| Project/Area Number |
61580026
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
Informatics
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| Research Institution | Osaka University |
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Principal Investigator |
MIZOGUCHI Riichiro The Institute of Scientific and Industrial Research, Osaka University, 産業科学研究所, 助教授 (20116106)
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| Project Period (FY) |
1986 – 1987
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| Project Status |
Completed (Fiscal Year 1987)
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| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1987: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1986: ¥1,600,000 (Direct Cost: ¥1,600,000)
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| Keywords | Knowledge base / Continuous speech recofnition / Environment for knowledge base construction / 知識獲得 / 知識工学 / 支援環境 / マン・マシンインタフェイス / 認識ルールデータベース / 音声データベース |
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| Research Abstract |
The main objective of our research is to construct a knowledge base for continuous speech recognition and its support environment. The system simulates the behavior of a human expert who can read the trajectories of feature parameters such as formant frequencies and power. The expertise is embedded in the knowledge base in the form of production rules. The environment is composed of four components such as speech database, rule database, rule translator and interface module. Speech database stores speech data with right segment labels and gives appropriate ones on request. Rule database stores some documents of rules such as name of the author and execution history which provides with pointers to data in speech database. It also manages versions of rules, which plays an important role in rule modification. Rule translator translates rules written in a highlevel rule language designed by us into OPS5 codes. Interface module integrates the above three components into a unified system and enables sophysticated interactions.
We obtained segmentation rate of 95% and recognition rate of 90% given the correct phoneme boundaries for five kinds of continuous speech uttered by six male udalts. The environment reduces the rule development time to less than one tenth of the previous one. Furtheremore, most of the rules were reorganized with the aid of the environment and the number of the rules were recuced to 70% of the original knowledge base retaining the recognition rate. All the results of the research contribute to the first step to establishment of a new methodology of speech recognition basd on knowledge engineering techniques.
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Report
(2 results)
Research Products
(15 results)
