The Unsupervised Acquisition of a Lexicon from Continuous Speech

dc.creatorde Marcken, Carl
dc.date1995-12-13
dc.date.accessioned2026-07-07T09:10:04Z
dc.date.available2026-07-07T09:10:04Z
dc.descriptionWe present an unsupervised learning algorithm that acquires a natural-language lexicon from raw speech. The algorithm is based on the optimal encoding of symbol sequences in an MDL framework, and uses a hierarchical representation of language that overcomes many of the problems that have stymied previous grammar-induction procedures. The forward mapping from symbol sequences to the speech stream is modeled using features based on articulatory gestures. We present results on the acquisition of lexicons and language models from raw speech, text, and phonetic transcripts, and demonstrate that our algorithm compares very favorably to other reported results with respect to segmentation performance and statistical efficiency.
dc.description27 page technical report
dc.identifierhttps://arxiv.org/abs/cmp-lg/9512002
dc.identifierhttp://arxiv.org/abs/cmp-lg/9512002
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151252
dc.subjectComputation and Language
dc.titleThe Unsupervised Acquisition of a Lexicon from Continuous Speech
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