Deep Active Speech Cancellation with Multi-Band Mamba Network

• URL: http://arxiv.org/abs/2502.01185v1
• Date: Mon, 03 Feb 2025 09:22:26 GMT
• Title: Deep Active Speech Cancellation with Multi-Band Mamba Network
• Authors: Yehuda Mishaly, Lior Wolf, Eliya Nachmani,
• Abstract summary: We present a novel deep learning network for Active Speech Cancellation (ASC) The proposed Multi-Band Mamba architecture segments input audio into distinct frequency bands, enabling precise anti-signal generation. Experimental results demonstrate substantial performance gains, achieving up to 7.2dB improvement in ANC scenarios and 6.2dB in ASC.
• Score: 62.73250985838971
• License:
• Abstract: We present a novel deep learning network for Active Speech Cancellation (ASC), advancing beyond Active Noise Cancellation (ANC) methods by effectively canceling both noise and speech signals. The proposed Multi-Band Mamba architecture segments input audio into distinct frequency bands, enabling precise anti-signal generation and improved phase alignment across frequencies. Additionally, we introduce an optimization-driven loss function that provides near-optimal supervisory signals for anti-signal generation. Experimental results demonstrate substantial performance gains, achieving up to 7.2dB improvement in ANC scenarios and 6.2dB in ASC, significantly outperforming existing methods. Audio samples are available at https://mishalydev.github.io/DeepASC-Demo

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