Voice Activity Detection Using Neural Network
Summary :
Voice activity detection (VAD) is to determine whether a short time speech frame is voice or silence. VAD is useful in reducing the mean speech coding rate by suppressing transmission during silence periods, and is effective in transmitting speech and other data simultaneously. This letter describes a VAD system that uses a neural network. The neural network gets several parameters by analyzing slices of the speech wave form, and outputs only one scalar value related to voice activity. This output is compared to a threshold to determine whether the slice is voice or silence. The mean code transfer rate can be reduced to less than 50% by using the proposed VAD system.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E81-B No.12 pp.2509-2513
- Publication Date
- 1998/12/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section LETTER (Special Issue on the Latest Development of Telecommunication Research)
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Jotaro IKEDO, "Voice Activity Detection Using Neural Network" in IEICE TRANSACTIONS on Communications,
vol. E81-B, no. 12, pp. 2509-2513, December 1998, doi: .
Abstract: Voice activity detection (VAD) is to determine whether a short time speech frame is voice or silence. VAD is useful in reducing the mean speech coding rate by suppressing transmission during silence periods, and is effective in transmitting speech and other data simultaneously. This letter describes a VAD system that uses a neural network. The neural network gets several parameters by analyzing slices of the speech wave form, and outputs only one scalar value related to voice activity. This output is compared to a threshold to determine whether the slice is voice or silence. The mean code transfer rate can be reduced to less than 50% by using the proposed VAD system.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e81-b_12_2509/_p
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@ARTICLE{e81-b_12_2509,
author={Jotaro IKEDO, },
journal={IEICE TRANSACTIONS on Communications},
title={Voice Activity Detection Using Neural Network},
year={1998},
volume={E81-B},
number={12},
pages={2509-2513},
abstract={Voice activity detection (VAD) is to determine whether a short time speech frame is voice or silence. VAD is useful in reducing the mean speech coding rate by suppressing transmission during silence periods, and is effective in transmitting speech and other data simultaneously. This letter describes a VAD system that uses a neural network. The neural network gets several parameters by analyzing slices of the speech wave form, and outputs only one scalar value related to voice activity. This output is compared to a threshold to determine whether the slice is voice or silence. The mean code transfer rate can be reduced to less than 50% by using the proposed VAD system.},
keywords={},
doi={},
ISSN={},
month={December},}
Copy
TY - JOUR
TI - Voice Activity Detection Using Neural Network
T2 - IEICE TRANSACTIONS on Communications
SP - 2509
EP - 2513
AU - Jotaro IKEDO
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E81-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 1998
AB - Voice activity detection (VAD) is to determine whether a short time speech frame is voice or silence. VAD is useful in reducing the mean speech coding rate by suppressing transmission during silence periods, and is effective in transmitting speech and other data simultaneously. This letter describes a VAD system that uses a neural network. The neural network gets several parameters by analyzing slices of the speech wave form, and outputs only one scalar value related to voice activity. This output is compared to a threshold to determine whether the slice is voice or silence. The mean code transfer rate can be reduced to less than 50% by using the proposed VAD system.
ER -
English
