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Journal Article Intra- and Inter-Frame Features for Automatic Speech Recognition
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Authors
Sung Joo Lee, Byung Ok Kang, Hoon Chung, Yunkeun Lee
Issue Date
2014-06
Citation
ETRI Journal, v.36, no.3, pp.514-517
ISSN
1225-6463
Publisher
한국전자통신연구원 (ETRI)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.4218/etrij.14.0213.0181
Project Code
14MS1500, Development of dialog-based spontaneous speech interface technology on mobile platform , Lee Yunkeun
Abstract
In this paper, alternative dynamic features for speech recognition are proposed. The goal of this work is to improve speech recognition accuracy by deriving the representation of distinctive dynamic characteristics from a speech spectrum. This work was inspired by two temporal dynamics of a speech signal. One is the highly non-stationary nature of speech, and the other is the inter-frame change of a speech spectrum. We adopt the use of a sub-frame spectrum analyzer to capture very rapid spectral changes within a speech analysis frame. In addition, we attempt to measure spectral fluctuations of a more complex manner as opposed to traditional dynamic features such as delta or double-delta. To evaluate the proposed features, speech recognition tests over smartphone environments were conducted. The experimental results show that the feature streams simply combined with the proposed features are effective for an improvement in the recognition accuracy of a hidden Markov model-based speech recognizer. © 2014 ETRI.
KSP Keywords
Dynamic features, Inter-frame, Non-Stationary, Spectral changes, Spectrum analyzer, Speech Signals, Speech analysis, Speech recognition accuracy, Sub-Frame, Temporal Dynamics, automatic speech recognition(ASR)