Statistical information and coarticulation as cues to word boundaries: a matter of signal quality

• Tipo: Artigo em Revista Científica Internacional
• Data: 2007

Autores

Tânia Fernandes (Autor) FPCEUP; Paulo Ventura (Autor) Outra; Régine Kolinsky (Autor) Outra

Revista

Título: PERCEPTION & PSYCHOPHYSICS

Vol. 69 Nº 6

Páginas: 856-864

ISSN: 0031-5117

Editora: Psychonomic Society Inc.

Indexação

ISI Web of Knowledge - 10 Citações

ISI Web of Science

Scopus - 14 Citações

Classificação Científica

FOS: Ciências sociais > Psicologia

Outras Informações

ID Authenticus: P-004-8MQ

DOI: 10.3758/BF03193922

Abstract (EN): We investigated how statistical information in the form of transitional probabilities (TPs) interacts with coarticulation, another sublexical cue to word boundaries, and examined the impact of signal quality on the weighting of these cues. In an artificial-language-learning setting, with phonetically intact speech, coarticulation overruled TPs, suggesting the predominance of subsegmental, low-level information. However, whereas the role of coarticulation in segmentation was highly modulated by signal quality, TPs were very resilient to noise. When coarticulation was rendered unreliable by strongly degrading the input with a 10-dB signal-to-noise ratio (SNR), only statistical information drove segmentation. In a more mildly degraded 22-dB SNR condition, in which some acoustic properties were still available, coarticulation was exploited, although with less reliability than in optimal conditions. These results can be interpreted according to a hierarchical approach (Mattys, White, & Melhom, 2005) in which both the available segmentation cues and the listening conditions have an important role in speech segmentation.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

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Nº de páginas: 9