Publications – Details
Speech-Codebook Based Soft Voice Activity Detection
- Authors:
- Florian Heese, Markus Niermann, and Peter Vary
- Book Title:
- Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
- Venue:
- Brisbane, QLD, Australia
- Event Date:
- 19.-24.4.2015
- Organization:
- IEEE
- Location:
- Piscataway, NJ, USA
- Date:
- Apr. 2015
- Language:
- English
Abstract
A novel noise-robust soft Voice Activity Detector (VAD) operating in
the short-time Fourier domain is presented. A speech energy gain is
obtained by frame-wise processing of a noisy speech signal with a
speech codebook algorithm. This gain can be used for robust voice
detection. A speaker-independent speech codebook, consisting of
spectral envelopes, is created in the training process. While
applying the algorithm, the codebook is adapted in every frame to
the current speaker by combining the harmonic pitch structure of the
actual noisy speech frame with the codebook entries. Soft VAD
values ranging from zero to one are calculated by post-processing of
the speech gain which is obtained using gain shape vector
quantization. A binary VAD is carried out by applying a
threshold. The proposed method does not rely on noise
a-priori knowledge and is robust w.r.t. highly non-stationary
noise and adverse SNR conditions. In addition, it is possible to
compromise between the detection-rate and the false-alarm-rate by
varying a threshold without increasing the total number of
mis-detections. Compared to state-of-the-art VAD systems, the
proposed method is characterized by better detection-rates at
significant lower false-alarm-rates.
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