HYBRID PROBABILISTIC ADAPTATION MODE CONTROLLER FOR GENERALIZED SIDELOBE CANCELLER-BASED TARGET-DIRECTIONAL SPEECH ENHANCEMENT

Signal Separation

Přednášející: Seon Man Kim, Autoři: Seon Man Kim, Hong Kook Kim, Gwangju Institute of Science and Technology, Republic of Korea

In this paper, we propose a new adaptation mode controller (AMC) for a generalized sidelobe canceller (GSC) having prior knowledge of the direction-of-arrival (DOA) of a desired signal source. To this end, the DOA-based a posteriori target-to-non-target-directional signal ratio (TNR) is first estimated from spatial cues such as phase differences among multi-microphone signals. Next, the estimated TNR is utilized to estimate the target-directional-signal absence probability (TSAP) and presence probability (TSPP), which include global and local terms. The probabilities are then applied to control parameters of adaptive filters via AMC. The performance evaluation of target-directional speech by the proposed approach is carried out by the perceptual evaluation of speech quality (PESQ) scores, noise reduction (NR), and average signal-to-noise ratio (SNR) under car noise conditions with various SNRs from -5 to 20 dB. It is shown from the experiments that the proposed approach provides better results than the conventional AMC.

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