7 citations · 7 across the 9 of their papers we have counts for
12 papers · 1 filter
EffVOC: Low-Delay Efficient Speech Waveform Reconstruction from Spectral Representations Without Phase
Renzheng Shi, Simon Welker, Timo Gerkmann +1
The Griffin-Lim algorithm has been a seminal contribution for phase reconstruction from amplitude spectrograms, however, requiring (infinitely) high algorithmic delay. Its low-dela…
Diffusion Buffer for Online Generative Speech Enhancement
Bunlong Lay, Rostislav Makarov, Simon Welker +2
Online Speech Enhancement was mainly reserved for predictive models. A key advantage of these models is that for an incoming signal frame from a stream of data, the model is called…
Real-Time Streaming Mel Vocoding with Generative Flow Matching
Simon Welker, Tal Peer, Timo Gerkmann
The task of Mel vocoding, i.e., the inversion of a Mel magnitude spectrogram to an audio waveform, is still a key component in many text-to-speech (TTS) systems today. Based on gen…
Non-intrusive Speech Quality Assessment with Diffusion Models Trained on Clean Speech
Danilo de Oliveira, Julius Richter, Jean-Marie Lemercier +2
Diffusion models have found great success in generating high quality, natural samples of speech, but their potential for density estimation for speech has so far remained largely u…
Unsupervised Blind Joint Dereverberation and Room Acoustics Estimation with Diffusion Models
Jean-Marie Lemercier, Eloi Moliner, Simon Welker +2
This paper presents an unsupervised method for single-channel blind dereverberation and room impulse response (RIR) estimation, called BUDDy. The algorithm is rooted in Bayesian po…
EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation
Julius Richter, Yi-Chiao Wu, Steven Krenn +5
We release the EARS (Expressive Anechoic Recordings of Speech) dataset, a high-quality speech dataset comprising 107 speakers from diverse backgrounds, totaling in 100 hours of cle…