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 [BibTeX] [Marc21]
Neuromorphic Based Oscillatory Device for Incremental Syllable Boundary Detection
Type of publication: Conference paper
Citation: Hyafil_INTERSPEECH_2015
Publication status: Published
Booktitle: Proc. of Interspeech
Year: 2015
Month: September
Pages: 1191-1195
Publisher: ISCA
Location: Dresden, Germany
Crossref: Hyafil_Idiap-RR-14-2015:
Abstract: Syllables are considered as basic supra-segmental units, used mainly in prosodic modelling. It has long been thought that efficient syllabification algorithms may also provide valuable cues for improved segmental (acoustic) modelling. However, the best current syllabification methods work offline, considering the power envelope of whole utterance. In this paper we introduce a new method for detection of syllable boundaries based on a model of speech parsing into syllables by neural oscillations in human auditory cortex. Neural oscillations automatically lock to speech slow fluctuations that convey the syllabic rhythm. Similarly as humans encode speech incrementally, i.e., not considering future temporal context, the proposed method works incrementally as well. In addition, it is highly robust to noise. Syllabification performance for English and different noise conditions was compared to the existing Mermelstein and group delay algorithms. While the performance of the existing methods depend on the type of noise and signal to noise ratio, the performance of the proposed method is constant under all noise conditions.
Keywords: Speech Analysis
Projects Idiap
Authors Hyafil, Alexandre
Cernak, Milos
Added by: [UNK]
Total mark: 0
  • Hyafil_INTERSPEECH_2015.pdf