Perceptual speech modeling for noisy speech recognition

研究成果: Conference article

摘要

This paper proposes a perceptual modeling approach with a two-stage recognition to deal with the issues of recognition degradation in noisy environment. The auditory masking effect is used for speech enhancement and acoustic modeling in order to overcome the model inconsistencies between training speech and noisy input. In the two-stage recognition, the maximum a posteriori (MAP) based adaptation algorithm is used to incrementally adapt the noise model. In order to evaluate our proposed approach, a Mandarin keyword spotting system was constructed. The experimental results show our proposed method achieves a better recognition rate compared to the audible noise suppression (ANS) and parallel model combination (PMC) methods for both in 70km/hr (10.3dB) and 90km/hr (6.4dB) car environments.

原文English
頁(從 - 到)I/385-I/388
期刊ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
1
出版狀態Published - 2002 七月 11
事件2002 IEEE International Conference on Acustics, Speech, and Signal Processing - Orlando, FL, United States
持續時間: 2002 五月 132002 五月 17

指紋

Speech recognition
Speech intelligibility
Speech enhancement
Acoustic noise
Railroad cars
Acoustics
Degradation

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

引用此文

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abstract = "This paper proposes a perceptual modeling approach with a two-stage recognition to deal with the issues of recognition degradation in noisy environment. The auditory masking effect is used for speech enhancement and acoustic modeling in order to overcome the model inconsistencies between training speech and noisy input. In the two-stage recognition, the maximum a posteriori (MAP) based adaptation algorithm is used to incrementally adapt the noise model. In order to evaluate our proposed approach, a Mandarin keyword spotting system was constructed. The experimental results show our proposed method achieves a better recognition rate compared to the audible noise suppression (ANS) and parallel model combination (PMC) methods for both in 70km/hr (10.3dB) and 90km/hr (6.4dB) car environments.",
author = "Wu, {Chung Hsien} and Chiu, {Yu Hsien} and Huigan Lim",
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AB - This paper proposes a perceptual modeling approach with a two-stage recognition to deal with the issues of recognition degradation in noisy environment. The auditory masking effect is used for speech enhancement and acoustic modeling in order to overcome the model inconsistencies between training speech and noisy input. In the two-stage recognition, the maximum a posteriori (MAP) based adaptation algorithm is used to incrementally adapt the noise model. In order to evaluate our proposed approach, a Mandarin keyword spotting system was constructed. The experimental results show our proposed method achieves a better recognition rate compared to the audible noise suppression (ANS) and parallel model combination (PMC) methods for both in 70km/hr (10.3dB) and 90km/hr (6.4dB) car environments.

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