arXiv:2007.12581
Dereverberation using joint estimation of dry speech signal and acoustic system
원문 초록
The purpose of speech dereverberation is to remove quality-degrading effects of a time-invariant impulse response filter from the signal. In this report, we describe an approach to speech dereverberation that involves joint estimation of the dry speech signal and of the room impulse response. We explore deep learning models that apply to each task separately, and how these can be combined in a joint model with shared parameters.
함께 살펴볼 논문
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VINP: Variational Bayesian Inference with Neural Speech Prior for Joint ASR-Effective Speech Dereverberation and Blind RIR Identification
Unsupervised Blind Joint Dereverberation and Room Acoustics Estimation with Diffusion Models
AV-RIR: Audio-Visual Room Impulse Response Estimation
TeCANet: Temporal-Contextual Attention Network for Environment-Aware Speech Dereverberation
ReverbFX: A Dataset of Room Impulse Responses Derived from Reverb Effect Plugins for Singing Voice Dereverberation
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
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