Automatic Learning Of Fuzzy Production Rules For Stop Sound In Continuous Speech

G. Ippolito; L. Saitta

doi:10.1117/12.943170

14 June 1984 Automatic Learning Of Fuzzy Production Rules For Stop Sound In Continuous Speech

G. Ippolito, L. Saitta

Proceedings Volume 0485, Applications of Artificial Intelligence I; (1984) https://doi.org/10.1117/12.943170
Event: 1984 Technical Symposium East, 1984, Arlington, United States

Abstract

Phoneme hypothesization in continuous speech can be a difficult task, especially if speaker-independence should be achieved. In general, the interpretation of speech patterns involves the generation of hypotheses concerning possible phonemic transcription of syllable segments automatically extracted from a numerical representation of energy-time-frequency obtained by short-term spectral analysis of a spoken sentence. Each hypothesis is evaluated and a degree of worthiness is assigned to it in such a way that it can be further processed for hypothesizing words or syntactic or semantic structures of the sentence. Moreover, context dependencies among adjacent phonemes must be taken into account; for this purpose, segments of the order of the syllables are considered; in this way the context dependencies (at least in Italian) may only occurr within the speech unit selected. In this paper the method used for the recognition of stop sounds (/b/, /d/, /g/, /p/, /t/, /k/) is described; the system is organized as an expert system, in which various sources of knowledge cooperate. In particular, each expert contains a set of production rules, describing how the different phonemic hypotheses are related to phonetic or acoustic features.

Citation Download Citation

G. Ippolito and L. Saitta "Automatic Learning Of Fuzzy Production Rules For Stop Sound In Continuous Speech", Proc. SPIE 0485, Applications of Artificial Intelligence I, (14 June 1984); https://doi.org/10.1117/12.943170

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