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New research explores advanced speech enhancement using neural audio codecs · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Two new research papers explore advanced techniques for speech enhancement, focusing on methods that improve audio quality under challenging acoustic conditions. The first paper introduces a test-time adaptation approach that uses an autoregressive prior derived from a neural audio codec to regularize speech enhancement models, showing improved quality especially when training and testing conditions differ. The second paper proposes a masked autoregressive speech enhancement method that leverages continuous latent representations from neural audio codecs, demonstrating a flexible trade-off between performance and computational cost. AI

IMPACT These papers advance speech enhancement techniques by exploring novel uses of neural audio codecs and autoregressive models, potentially leading to improved audio clarity in various applications.

RANK_REASON Two academic papers published on arXiv detailing novel methods for speech enhancement.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New research explores advanced speech enhancement using neural audio codecs · 2 sources tracked

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Two academic papers published on arXiv detailing novel methods for speech enhancement.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Sofiene Kammoun, Simon Leglaive, Xavier Alameda-Pineda, Timo Gerkmann ·

    Test-time adaptation for speech enhancement with an autoregressive speech prior

    arXiv:2609.03622v1 Announce Type: cross Abstract: Test-time adaptation (TTA) offers a promising direction for improving speech enhancement models under mismatched acoustic conditions, without requiring access to labeled target data. In this work, we propose a single-utterance TTA…

  2. arXiv cs.AI TIER_1 English(EN) · Yoto Fujita, Simon Leglaive, Laurent Girin ·

    Masked Autoregressive Speech Enhancement with Continuous Neural Audio Codec Representations

    arXiv:2609.03940v1 Announce Type: cross Abstract: Most previous work on speech enhancement (SE) based on masked generative modeling relied on discrete token representations of audio signals, obtained using neural audio codecs (NACs). However, a recent study has shown that continu…

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