Speaker-independence and large lexicon access are still two of the greatest problems in automatic speech recognition. Cognitive and information-theory approaches try to solve the recognition problem by proceeding in almost opposite directions. The former rely on knowledge representation, reasoning and perceptual analysis, while the latter is in general based on highly numerical and mathematical algorithms. / Progress arises from the integration of the two mentioned approaches. Artificial intelligence techniques are often used in the cognitive approach, but these techniques usually lack sophisticated numerical support. The Extended Procedural Network constitutes a general AI framework which supports powerful numerical strategies which include stochastic techniques. / The model has been tested on difficult problems in speech recognition, including speaker-independent letter and digit recognition, speaker-independent vowel and diphthong recognition, and access to a large lexicon. / Various experiments and comparisons have been run on a large number of speakers and the results are reported. / A discussion of further research advancements and investigations is provided.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.75954 |
| Date | January 1989 |
| Creators | Merlo, Ettore |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Doctor of Philosophy (School of Computer Science.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 000910019, proquestno: AAINL52440, Theses scanned by UMI/ProQuest. |
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