As a preprocessor of the automatic speech recognizer in a noisy environment, a microphone array system has been investigated to reduce the environmental noise. In usual microphone array design, a plane wave is assumed for the sake of simplicity (far-field assumption). However, this far-field assumption does not always hold, resulting in distortion in the array output. In this report, the subspace method, which is one of the high resolution spectrum estimator, is applied to the near-field source localization problem. A high resolution method is necessary especially for the near-field source localization with a small-sized array. By combining the source localization technique with a spatial inverse filter, the signal coming from the multiple sources in the near-field range can be separated. The modified minimum variance beamformer is used to design the spatial inverse filter. As a result of the experiment in a real environment with two sound sources in the near-field range, 60-70% of word recognition rate was achieved.
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Futoshi ASANO, Hideki ASOH, Toshihiro MATSUI, "Sound Source Localization and Separation in Near Field" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 11, pp. 2286-2294, November 2000, doi: .
Abstract: As a preprocessor of the automatic speech recognizer in a noisy environment, a microphone array system has been investigated to reduce the environmental noise. In usual microphone array design, a plane wave is assumed for the sake of simplicity (far-field assumption). However, this far-field assumption does not always hold, resulting in distortion in the array output. In this report, the subspace method, which is one of the high resolution spectrum estimator, is applied to the near-field source localization problem. A high resolution method is necessary especially for the near-field source localization with a small-sized array. By combining the source localization technique with a spatial inverse filter, the signal coming from the multiple sources in the near-field range can be separated. The modified minimum variance beamformer is used to design the spatial inverse filter. As a result of the experiment in a real environment with two sound sources in the near-field range, 60-70% of word recognition rate was achieved.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_11_2286/_p
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@ARTICLE{e83-a_11_2286,
author={Futoshi ASANO, Hideki ASOH, Toshihiro MATSUI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Sound Source Localization and Separation in Near Field},
year={2000},
volume={E83-A},
number={11},
pages={2286-2294},
abstract={As a preprocessor of the automatic speech recognizer in a noisy environment, a microphone array system has been investigated to reduce the environmental noise. In usual microphone array design, a plane wave is assumed for the sake of simplicity (far-field assumption). However, this far-field assumption does not always hold, resulting in distortion in the array output. In this report, the subspace method, which is one of the high resolution spectrum estimator, is applied to the near-field source localization problem. A high resolution method is necessary especially for the near-field source localization with a small-sized array. By combining the source localization technique with a spatial inverse filter, the signal coming from the multiple sources in the near-field range can be separated. The modified minimum variance beamformer is used to design the spatial inverse filter. As a result of the experiment in a real environment with two sound sources in the near-field range, 60-70% of word recognition rate was achieved.},
keywords={},
doi={},
ISSN={},
month={November},}
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TY - JOUR
TI - Sound Source Localization and Separation in Near Field
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2286
EP - 2294
AU - Futoshi ASANO
AU - Hideki ASOH
AU - Toshihiro MATSUI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2000
AB - As a preprocessor of the automatic speech recognizer in a noisy environment, a microphone array system has been investigated to reduce the environmental noise. In usual microphone array design, a plane wave is assumed for the sake of simplicity (far-field assumption). However, this far-field assumption does not always hold, resulting in distortion in the array output. In this report, the subspace method, which is one of the high resolution spectrum estimator, is applied to the near-field source localization problem. A high resolution method is necessary especially for the near-field source localization with a small-sized array. By combining the source localization technique with a spatial inverse filter, the signal coming from the multiple sources in the near-field range can be separated. The modified minimum variance beamformer is used to design the spatial inverse filter. As a result of the experiment in a real environment with two sound sources in the near-field range, 60-70% of word recognition rate was achieved.
ER -