127 citations · 191 across the 6 of their papers we have counts for
6 papers
On TasNet for Low-Latency Single-Speaker Speech Enhancement
Morten Kolbæk, Zheng-Hua Tan, Søren Holdt Jensen +1
In recent years, speech processing algorithms have seen tremendous progress primarily due to the deep learning renaissance. This is especially true for speech separation where the…
On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement
Morten Kolbæk, Zheng-Hua Tan, Søren Holdt Jensen +1
Many deep learning-based speech enhancement algorithms are designed to minimize the mean-square error (MSE) in some transform domain between a predicted and a target speech signal.…
On the Relationship Between Short-Time Objective Intelligibility and Short-Time Spectral-Amplitude Mean-Square Error for Speech Enhancement
Morten Kolbæk, Zheng-Hua Tan, Jesper Jensen
The majority of deep neural network (DNN) based speech enhancement algorithms rely on the mean-square error (MSE) criterion of short-time spectral amplitudes (STSA), which has no a…
Monaural Speech Enhancement using Deep Neural Networks by Maximizing a Short-Time Objective Intelligibility Measure
Morten Kolbæk, Zheng-Hua Tan, Jesper Jensen
In this paper we propose a Deep Neural Network (DNN) based Speech Enhancement (SE) system that is designed to maximize an approximation of the Short-Time Objective Intelligibility…
Joint Separation and Denoising of Noisy Multi-talker Speech using Recurrent Neural Networks and Permutation Invariant Training
Morten Kolbæk, Dong Yu, Zheng-Hua Tan +1
In this paper we propose to use utterance-level Permutation Invariant Training (uPIT) for speaker independent multi-talker speech separation and denoising, simultaneously. Specific…
Permutation Invariant Training of Deep Models for Speaker-Independent Multi-talker Speech Separation
Dong Yu, Morten Kolbæk, Zheng-Hua Tan +1
We propose a novel deep learning model, which supports permutation invariant training (PIT), for speaker independent multi-talker speech separation, commonly known as the cocktail-…