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Found 4 papers, 1 papers with code
HD-DEMUCS: General Speech Restoration with Heterogeneous Decoders
This paper introduces an end-to-end neural speech restoration model, HD-DEMUCS, demonstrating efficacy across multiple distortion environments.
Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting
In this paper, we propose a novel end-to-end user-defined keyword spotting method that utilizes linguistically corresponding patterns between speech and text sequences.
Phase Continuity: Learning Derivatives of Phase Spectrum for Speech Enhancement
Modern neural speech enhancement models usually include various forms of phase information in their training loss terms, either explicitly or implicitly.
MIRNet: Learning multiple identities representations in overlapped speech
Many approaches can derive information about a single speaker's identity from the speech by learning to recognize consistent characteristics of acoustic parameters.
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