0000000000026398
AUTHOR
Emilio Sanchis
Application of the Error Correcting Grammatical Inference Method (ECGI) to Multi-Speaker Isolated Word Recognition
It is well known that speech signals constitute highly structured objects which are composed of different kinds of subobjects such as words, phonemes, etc. This fact has motivated several researchers to propose different models which more or less explicitly assume the structural nature of speech. Notable examples of these models are Markov models /Bak 75/, /Jel 76/; the famous Harpy /Low 76/; Scriber and Lafs /Kla 80/; and many others works in which the convenience of some structural model of the speech objects considered is explicitly claimed /Gup 82/, /Lev 83/, /Cra 84/, /Sca 85/, /Kam 85/, /Sau 85/, /Rab 85/, /Kop 85/, /Sch 85/, /Der 86/, /Tan 86/.
A General Fuzzy-Parsing Scheme for Speech Recognition
In this paper a Speech Recognition Methodology is proposed which is based on the general assumption of ‘fuzzyness’ of both speech-data and knowledge-sources. Besides this general principle, there are other fundamental assumptions which are also the bases of the proposed methodology: ‘Modularity’ in the knowledge organization, ‘Homogeneity’ in the representation of data and knowledge, ‘Passiveness’ of the ‘understanding flow’ (no backtraking or feedback), and ‘Parallelism’ in the recognition activity.