Reducing Speech Noise for Patients with Dysarthria in Noisy Environments
Summary :
Dysarthric speech results from damage to the central nervous system involving the articulator, which can mainly be characterized by poor articulation due to irregular sub-glottal pressure, loudness bursts, phoneme elongation, and unexpected pauses during utterances. Since dysarthric speakers have physical disabilities due to the impairment of their nervous system, they cannot easily control electronic devices. For this reason, automatic speech recognition (ASR) can be a convenient interface for dysarthric speakers to control electronic devices. However, the performance of dysarthric ASR severely degrades when there is background noise. Thus, in this paper, we propose a noise reduction method that improves the performance of dysarthric ASR. The proposed method selectively applies either a Wiener filtering algorithm or a Kalman filtering algorithm according to the result of voiced or unvoiced classification. Then, the performance of the proposed method is compared to a conventional Wiener filtering method in terms of ASR accuracy.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.11 pp.2881-2887
- Publication Date
- 2014/11/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDP7130
- Type of Manuscript
- PAPER
- Category
- Speech and Hearing
Authors
Woo KYEONG SEONG
Gwangju Institute of Science and Technology (GIST)
Ji HUN PARK
Samsung Electronics
Hong KOOK KIM
Gwangju Institute of Science and Technology (GIST)
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Woo KYEONG SEONG, Ji HUN PARK, Hong KOOK KIM, "Reducing Speech Noise for Patients with Dysarthria in Noisy Environments" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 11, pp. 2881-2887, November 2014, doi: 10.1587/transinf.2014EDP7130.
Abstract: Dysarthric speech results from damage to the central nervous system involving the articulator, which can mainly be characterized by poor articulation due to irregular sub-glottal pressure, loudness bursts, phoneme elongation, and unexpected pauses during utterances. Since dysarthric speakers have physical disabilities due to the impairment of their nervous system, they cannot easily control electronic devices. For this reason, automatic speech recognition (ASR) can be a convenient interface for dysarthric speakers to control electronic devices. However, the performance of dysarthric ASR severely degrades when there is background noise. Thus, in this paper, we propose a noise reduction method that improves the performance of dysarthric ASR. The proposed method selectively applies either a Wiener filtering algorithm or a Kalman filtering algorithm according to the result of voiced or unvoiced classification. Then, the performance of the proposed method is compared to a conventional Wiener filtering method in terms of ASR accuracy.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDP7130/_p
Copy
@ARTICLE{e97-d_11_2881,
author={Woo KYEONG SEONG, Ji HUN PARK, Hong KOOK KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Reducing Speech Noise for Patients with Dysarthria in Noisy Environments},
year={2014},
volume={E97-D},
number={11},
pages={2881-2887},
abstract={Dysarthric speech results from damage to the central nervous system involving the articulator, which can mainly be characterized by poor articulation due to irregular sub-glottal pressure, loudness bursts, phoneme elongation, and unexpected pauses during utterances. Since dysarthric speakers have physical disabilities due to the impairment of their nervous system, they cannot easily control electronic devices. For this reason, automatic speech recognition (ASR) can be a convenient interface for dysarthric speakers to control electronic devices. However, the performance of dysarthric ASR severely degrades when there is background noise. Thus, in this paper, we propose a noise reduction method that improves the performance of dysarthric ASR. The proposed method selectively applies either a Wiener filtering algorithm or a Kalman filtering algorithm according to the result of voiced or unvoiced classification. Then, the performance of the proposed method is compared to a conventional Wiener filtering method in terms of ASR accuracy.},
keywords={},
doi={10.1587/transinf.2014EDP7130},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - Reducing Speech Noise for Patients with Dysarthria in Noisy Environments
T2 - IEICE TRANSACTIONS on Information
SP - 2881
EP - 2887
AU - Woo KYEONG SEONG
AU - Ji HUN PARK
AU - Hong KOOK KIM
PY - 2014
DO - 10.1587/transinf.2014EDP7130
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2014
AB - Dysarthric speech results from damage to the central nervous system involving the articulator, which can mainly be characterized by poor articulation due to irregular sub-glottal pressure, loudness bursts, phoneme elongation, and unexpected pauses during utterances. Since dysarthric speakers have physical disabilities due to the impairment of their nervous system, they cannot easily control electronic devices. For this reason, automatic speech recognition (ASR) can be a convenient interface for dysarthric speakers to control electronic devices. However, the performance of dysarthric ASR severely degrades when there is background noise. Thus, in this paper, we propose a noise reduction method that improves the performance of dysarthric ASR. The proposed method selectively applies either a Wiener filtering algorithm or a Kalman filtering algorithm according to the result of voiced or unvoiced classification. Then, the performance of the proposed method is compared to a conventional Wiener filtering method in terms of ASR accuracy.
ER -
English
