257 citations · 969 across the 53 of their papers we have counts for
17 papers · 2 filters
Distilling HuBERT with LSTMs via Decoupled Knowledge Distillation
Danilo de Oliveira, Timo Gerkmann
Much research effort is being applied to the task of compressing the knowledge of self-supervised models, which are powerful, yet large and memory consuming. In this work, we show…
A Flexible Online Framework for Projection-Based STFT Phase Retrieval
Tal Peer, Simon Welker, Johannes Kolhoff +1
Several recent contributions in the field of iterative STFT phase retrieval have demonstrated that the performance of the classical Griffin-Lim method can be considerably improved…
Single and Few-step Diffusion for Generative Speech Enhancement
Bunlong Lay, Jean-Marie Lemercier, Julius Richter +1
Diffusion models have shown promising results in speech enhancement, using a task-adapted diffusion process for the conditional generation of clean speech given a noisy mixture. Ho…
EMOCONV-DIFF: Diffusion-based Speech Emotion Conversion for Non-parallel and In-the-wild Data
Navin Raj Prabhu, Bunlong Lay, Simon Welker +2
Speech emotion conversion is the task of converting the expressed emotion of a spoken utterance to a target emotion while preserving the lexical content and speaker identity. While…
Diffusion Posterior Sampling for Informed Single-Channel Dereverberation
Jean-Marie Lemercier, Simon Welker, Timo Gerkmann
We present in this paper an informed single-channel dereverberation method based on conditional generation with diffusion models. With knowledge of the room impulse response, the a…
On the Behavior of Intrusive and Non-intrusive Speech Enhancement Metrics in Predictive and Generative Settings
Danilo de Oliveira, Julius Richter, Jean-Marie Lemercier +2
Since its inception, the field of deep speech enhancement has been dominated by predictive (discriminative) approaches, such as spectral mapping or masking. Recently, however, nove…