Refinement of Landmark Detection and Extraction of Articulator-Free Features for Knowledge-Based Speech Recognition

Jung-In LEE
Jeung-Yoon CHOI
Hong-Goo KANG

IEICE TRANSACTIONS on Information and Systems   Vol.E96-D    No.3    pp.746-749
Publication Date: 2013/03/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.746
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
speech recognition,  acoustic events,  landmark detection,  

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Refinement methods for landmark detection and extraction of articulator-free features for a knowledge-based speech recognition system are described. Sub-band energy difference profiles are used to detect landmarks, with additional parameters used to improve accuracy. For articulator-free feature extraction, duration, relative energy, and silence detection are additionally used to find [continuant] and [strident] features. Vowel, obstruent and sonorant consonant landmarks, and locations of voicing onsets and offsets are detected within a unified framework with 85% accuracy overall. Additionally, 75% and 79% of [continuant] and [strident] features, respectively, are detected from landmarks.