상세정보
학술지
Online Blind Channel Normalization Using BPF-Based Modulation Frequency Filtering
- 발행일
- 201612
- 출처
- ETRI Journal, v.38 no.6, pp.1190-1196
- ISSN
- 1225-6463
- 출판사
- 한국전자통신연구원 (ETRI)
- 협약과제
- 15MS9500, 언어학습을 위한 자유발화형 음성대화처리 원천기술 개발, 이윤근
- 초록
- We propose a new bandpass filter (BPF)-based online channel normalization method to dynamically suppress channel distortion when the speech and channel noise components are unknown. In this method, an adaptive modulation frequency filter is used to perform channel normalization, whereas conventional modulation filtering methods apply the same filter form to each utterance. In this paper, we only normalize the two mel frequency cepstral coefficients (C0 and C1) with large dynamic ranges; the computational complexity is thus decreased, and channel normalization accuracy is improved. Additionally, to update the filter weights dynamically, we normalize the learning rates using the dimensional power of each frame. Our speech recognition experiments using the proposed BPF-based blind channel normalization method show that this approach effectively removes channel distortion and results in only a minor decline in accuracy when online channel normalization processing is used instead of batch processing.
- KSP 제안 키워드
- Band-pass filter(BPF), Batch processing, Computational complexity, Filtering method, Frequency cepstral coefficients, Mel-Frequency Cepstrum Coefficients(MFCC), Modulation frequency, Noise components, Normalization method, adaptive modulation, channel noise