Research
ML Applications
Environment-aware Reconfigurable Noise Suppression
April 9, 2020
Abstract
The paper proposes an efficient, robust, and reconfigurable technique to suppress various types of noises for any sampling rate. The theoretical analyses, subjective and objective test results show that the proposed noise suppression (NS) solution significantly enhances the speech transmission index (STI), speech intelligibility (SI), signal-to-noise ratio (SNR), and subjective listening experience. The STI and SI consists of 5 levels, i.e., bad, poor, fair, good, and excellent. The most common noisy condition is of SNR ranging from -5 to 8 dB. For the input SNR between -5 and 2.5 dB, the proposed NS improves the STI and SI from “fair” to “good”. For the input SNR between 2.5 to 8 dB, the STI and SI are improved from “good” to “excellent” by the proposed NS. The proposed NS can be adopted in both capture and playback paths for voice over internet protocol, voice-trigger, and automatic speech recognition applications.
AUTHORS
Written by
Jun Yang
Joshua Bingham
Publisher
International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
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