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SpeechPainter: Text-conditioned Speech Inpainting

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arxiv 2202.07273 v2 pith:LG2CFNMF submitted 2022-02-15 cs.SD cs.LGeess.AS

Zalán Borsos , Matt Sharifi , Marco Tagliasacchi This is my paper · ORCID
classification cs.SDcs.LGeess.AS
keywords speechinpaintingmodelspeechpainteradaptiveapproachappropriateauxiliary
verification ladder T0 review T1 audit T2 compute T3 formal
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We propose SpeechPainter, a model for filling in gaps of up to one second in speech samples by leveraging an auxiliary textual input. We demonstrate that the model performs speech inpainting with the appropriate content, while maintaining speaker identity, prosody and recording environment conditions, and generalizing to unseen speakers. Our approach significantly outperforms baselines constructed using adaptive TTS, as judged by human raters in side-by-side preference and MOS tests.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Multi Codec Discrete Diffusion Model for Text Guided Speech Inpainting and Editing

    cs.SD 2026-08 conditional novelty 6.0 of 10

    A multi-codebook discrete diffusion model with coarse-to-fine RVQ generation and span-localized guidance improves speech inpainting and editing on RealEdit.

  2. A2SB: Audio-to-Audio Schrodinger Bridges

    cs.SD 2025-01 conditional novelty 6.0 of 10

    A2SB applies Schrödinger bridges to music restoration, achieving state-of-the-art bandwidth extension and inpainting at 44.1kHz in a single vocoder-free model.

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