A Speech Enhancement Method Based on the Combination of Microphone Array and Parabolic Reflector
×
Cite This
Citation & Abstract
Y. Geng, T. Zhang, ME. SA. Yaw, and H. Wang, "A Speech Enhancement Method Based on the Combination of Microphone Array and Parabolic Reflector," J. Audio Eng. Soc., vol. 70, no. 1/2, pp. 5-23, (2022 January.). doi: https://doi.org/10.17743/jaes.2021.0047
Y. Geng, T. Zhang, ME. SA. Yaw, and H. Wang, "A Speech Enhancement Method Based on the Combination of Microphone Array and Parabolic Reflector," J. Audio Eng. Soc., vol. 70 Issue 1/2 pp. 5-23, (2022 January.). doi: https://doi.org/10.17743/jaes.2021.0047
Abstract: Speech enhancement is an essential aspect of the field of speech processing research. In most cases the performance of back-end speech technology (such as speech recognition) depends on the quality of speech enhancement output. One typical multi-channel speech enhancement method is microphone array beamforming. However the beamforming performance decreases when it works in a low Signal-to-Noise Ratio (SNR) environment. We propose a speech enhancement method called Paraboloid with Microphone Array (PMA) to improve the microphone array performance. The PMA is a combination enhancement method. It combines a beamforming speech enhancement modular and an acoustic enhancement modular achieved by a paraboloid. This method can be described as follows: (1) The target signal is enhanced by the microphone array and the acoustic focusing method, which we achieved by attaching a circular microphone array to a paraboloid. These two methods enhance the signal from different perspectives, thus making the enhanced signals complementary. (2) We employ the Independent Component Analysis (ICA) method to combine the output from the two abovementioned methods, which achieved the speech signal's secondary enhancement. In this study we analyze the speech enhancement property of the parabolic quantitatively. Computer simulation shows that the proposed method performs well in the low Signal-to-Noise Ratio (SNR) environment. The real-world experimental results are similar to the computer simulation results. Besides, the subjective experiments also verify the feasibility of the proposed method.
@article{geng2022a,
author={geng, yanzhang and zhang, tao and yaw, mensah samuel and wang, heng},
journal={journal of the audio engineering society},
title={a speech enhancement method based on the combination of microphone array and parabolic reflector},
year={2022},
volume={70},
number={1/2},
pages={5-23},
doi={https://doi.org/10.17743/jaes.2021.0047},
month={january},}
@article{geng2022a,
author={geng, yanzhang and zhang, tao and yaw, mensah samuel and wang, heng},
journal={journal of the audio engineering society},
title={a speech enhancement method based on the combination of microphone array and parabolic reflector},
year={2022},
volume={70},
number={1/2},
pages={5-23},
doi={https://doi.org/10.17743/jaes.2021.0047},
month={january},
abstract={speech enhancement is an essential aspect of the field of speech processing research. in most cases the performance of back-end speech technology (such as speech recognition) depends on the quality of speech enhancement output. one typical multi-channel speech enhancement method is microphone array beamforming. however the beamforming performance decreases when it works in a low signal-to-noise ratio (snr) environment. we propose a speech enhancement method called paraboloid with microphone array (pma) to improve the microphone array performance. the pma is a combination enhancement method. it combines a beamforming speech enhancement modular and an acoustic enhancement modular achieved by a paraboloid. this method can be described as follows: (1) the target signal is enhanced by the microphone array and the acoustic focusing method, which we achieved by attaching a circular microphone array to a paraboloid. these two methods enhance the signal from different perspectives, thus making the enhanced signals complementary. (2) we employ the independent component analysis (ica) method to combine the output from the two abovementioned methods, which achieved the speech signal's secondary enhancement. in this study we analyze the speech enhancement property of the parabolic quantitatively. computer simulation shows that the proposed method performs well in the low signal-to-noise ratio (snr) environment. the real-world experimental results are similar to the computer simulation results. besides, the subjective experiments also verify the feasibility of the proposed method.},}
TY - paper
TI - A Speech Enhancement Method Based on the Combination of Microphone Array and Parabolic Reflector
SP - 5
EP - 23
AU - Geng, Yanzhang
AU - Zhang, Tao
AU - Yaw, Mensah Samuel
AU - Wang, Heng
PY - 2022
JO - Journal of the Audio Engineering Society
IS - 1/2
VO - 70
VL - 70
Y1 - January 2022
TY - paper
TI - A Speech Enhancement Method Based on the Combination of Microphone Array and Parabolic Reflector
SP - 5
EP - 23
AU - Geng, Yanzhang
AU - Zhang, Tao
AU - Yaw, Mensah Samuel
AU - Wang, Heng
PY - 2022
JO - Journal of the Audio Engineering Society
IS - 1/2
VO - 70
VL - 70
Y1 - January 2022
AB - Speech enhancement is an essential aspect of the field of speech processing research. In most cases the performance of back-end speech technology (such as speech recognition) depends on the quality of speech enhancement output. One typical multi-channel speech enhancement method is microphone array beamforming. However the beamforming performance decreases when it works in a low Signal-to-Noise Ratio (SNR) environment. We propose a speech enhancement method called Paraboloid with Microphone Array (PMA) to improve the microphone array performance. The PMA is a combination enhancement method. It combines a beamforming speech enhancement modular and an acoustic enhancement modular achieved by a paraboloid. This method can be described as follows: (1) The target signal is enhanced by the microphone array and the acoustic focusing method, which we achieved by attaching a circular microphone array to a paraboloid. These two methods enhance the signal from different perspectives, thus making the enhanced signals complementary. (2) We employ the Independent Component Analysis (ICA) method to combine the output from the two abovementioned methods, which achieved the speech signal's secondary enhancement. In this study we analyze the speech enhancement property of the parabolic quantitatively. Computer simulation shows that the proposed method performs well in the low Signal-to-Noise Ratio (SNR) environment. The real-world experimental results are similar to the computer simulation results. Besides, the subjective experiments also verify the feasibility of the proposed method.
Speech enhancement is an essential aspect of the field of speech processing research. In most cases the performance of back-end speech technology (such as speech recognition) depends on the quality of speech enhancement output. One typical multi-channel speech enhancement method is microphone array beamforming. However the beamforming performance decreases when it works in a low Signal-to-Noise Ratio (SNR) environment. We propose a speech enhancement method called Paraboloid with Microphone Array (PMA) to improve the microphone array performance. The PMA is a combination enhancement method. It combines a beamforming speech enhancement modular and an acoustic enhancement modular achieved by a paraboloid. This method can be described as follows: (1) The target signal is enhanced by the microphone array and the acoustic focusing method, which we achieved by attaching a circular microphone array to a paraboloid. These two methods enhance the signal from different perspectives, thus making the enhanced signals complementary. (2) We employ the Independent Component Analysis (ICA) method to combine the output from the two abovementioned methods, which achieved the speech signal's secondary enhancement. In this study we analyze the speech enhancement property of the parabolic quantitatively. Computer simulation shows that the proposed method performs well in the low Signal-to-Noise Ratio (SNR) environment. The real-world experimental results are similar to the computer simulation results. Besides, the subjective experiments also verify the feasibility of the proposed method.
Authors:
Geng, Yanzhang; Zhang, Tao; Yaw, Mensah Samuel; Wang, Heng
Affiliation:
School of Electrical Information Engineering and the Texas Instruments DSP Collaboration Lab, Tianjin University, Tianjin, China JAES Volume 70 Issue 1/2 pp. 5-23; January 2022
Publication Date:
January 23, 2022Import into BibTeX
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=21547