65 citations · 96 across the 17 of their papers we have counts for
24 papers
ICASSP 2024 Speech Signal Improvement Challenge
Nicolae Catalin Ristea, Ando Saabas, Ross Cutler +3
The ICASSP 2024 Speech Signal Improvement Grand Challenge is intended to stimulate research in the area of improving the speech signal quality in communication systems. This marks…
ICASSP 2023 Acoustic Echo Cancellation Challenge
Ross Cutler, Ando Saabas, Tanel Parnamaa +7
The ICASSP 2023 Acoustic Echo Cancellation Challenge is intended to stimulate research in acoustic echo cancellation (AEC), which is an important area of speech enhancement and is…
Towards Real-Time Single-Channel Speech Separation in Noisy and Reverberant Environments
Julian Neri, Sebastian Braun
Real-time single-channel speech separation aims to unmix an audio stream captured from a single microphone that contains multiple people talking at once, environmental noise, and r…
ICASSP 2023 Deep Noise Suppression Challenge
Harishchandra Dubey, Ashkan Aazami, Vishak Gopal +9
Deep Speech Enhancement Challenge is the 5th edition of deep noise suppression (DNS) challenges organized at ICASSP 2023 Signal Processing Grand Challenges. DNS challenges were org…
ICASSP 2023 Speech Signal Improvement Challenge
Ross Cutler, Ando Saabas, Babak Naderi +3
The ICASSP 2023 Speech Signal Improvement Challenge is intended to stimulate research in the area of improving the speech signal quality in communication systems. The speech signal…
Task splitting for DNN-based acoustic echo and noise removal
Sebastian Braun, Maria Luis Valero
Neural networks have led to tremendous performance gains for single-task speech enhancement, such as noise suppression and acoustic echo cancellation (AEC). In this work, we evalua…
ICASSP 2022 Acoustic Echo Cancellation Challenge
Ross Cutler, Ando Saabas, Tanel Parnamaa +5
The ICASSP 2022 Acoustic Echo Cancellation Challenge is intended to stimulate research in acoustic echo cancellation (AEC), which is an important area of speech enhancement and sti…
ICASSP 2022 Deep Noise Suppression Challenge
Harishchandra Dubey, Vishak Gopal, Ross Cutler +8
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. This is the 4th DNS chal…
Effect of noise suppression losses on speech distortion and ASR performance
Sebastian Braun, Hannes Gamper
Deep learning based speech enhancement has made rapid development towards improving quality, while models are becoming more compact and usable for real-time on-the-edge inference.…
Unsupervised Speech Enhancement with speech recognition embedding and disentanglement losses
Viet Anh Trinh, Sebastian Braun
Speech enhancement has recently achieved great success with various deep learning methods. However, most conventional speech enhancement systems are trained with supervised methods…
Performance optimizations on deep noise suppression models
Jerry Chee, Sebastian Braun, Vishak Gopal +1
We study the role of magnitude structured pruning as an architecture search to speed up the inference time of a deep noise suppression (DNS) model. While deep learning approaches h…
Low complexity online convolutional beamforming
Sebastian Braun, Ivan Tashev
Convolutional beamformers integrate the multichannel linear prediction model into beamformers, which provide good performance and optimality for joint dereverberation and noise red…
On training targets for noise-robust voice activity detection
Sebastian Braun, Ivan Tashev
The task of voice activity detection (VAD) is an often required module in various speech processing, analysis and classification tasks. While state-of-the-art neural network based…
Towards efficient models for real-time deep noise suppression
Sebastian Braun, Hannes Gamper, Chandan K. A. Reddy +1
With recent research advancements, deep learning models are becoming attractive and powerful choices for speech enhancement in real-time applications. While state-of-the-art models…
Interspeech 2021 Deep Noise Suppression Challenge
Chandan K A Reddy, Harishchandra Dubey, Kazuhito Koishida +7
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. We recently organized a…
ICASSP 2021 Acoustic Echo Cancellation Challenge: Datasets, Testing Framework, and Results
Kusha Sridhar, Ross Cutler, Ando Saabas +6
The ICASSP 2021 Acoustic Echo Cancellation Challenge is intended to stimulate research in the area of acoustic echo cancellation (AEC), which is an important part of speech enhance…
ICASSP 2021 Deep Noise Suppression Challenge
Chandan K A Reddy, Harishchandra Dubey, Vishak Gopal +5
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. We recently organized a…
DBNET: DOA-driven beamforming network for end-to-end farfield sound source separation
Ali Aroudi, Sebastian Braun
Many deep learning techniques are available to perform source separation and reduce background noise. However, designing an end-to-end multi-channel source separation method using…
A consolidated view of loss functions for supervised deep learning-based speech enhancement
Sebastian Braun, Ivan Tashev
Deep learning-based speech enhancement for real-time applications recently made large advancements. Due to the lack of a tractable perceptual optimization target, many myths around…
Data augmentation and loss normalization for deep noise suppression
Sebastian Braun, Ivan Tashev
Speech enhancement using neural networks is recently receiving large attention in research and being integrated in commercial devices and applications. In this work, we investigate…
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results
Chandan K. A. Reddy, Vishak Gopal, Ross Cutler +10
The INTERSPEECH 2020 Deep Noise Suppression (DNS) Challenge is intended to promote collaborative research in real-time single-channel Speech Enhancement aimed to maximize the subje…
Weighted Speech Distortion Losses for Neural-network-based Real-time Speech Enhancement
Yangyang Xia, Sebastian Braun, Chandan K. A. Reddy +3
This paper investigates several aspects of training a RNN (recurrent neural network) that impact the objective and subjective quality of enhanced speech for real-time single-channe…
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework
Chandan K. A. Reddy, Ebrahim Beyrami, Harishchandra Dubey +10
The INTERSPEECH 2020 Deep Noise Suppression Challenge is intended to promote collaborative research in real-time single-channel Speech Enhancement aimed to maximize the subjective…
Predicting word error rate for reverberant speech
Hannes Gamper, Dimitra Emmanouilidou, Sebastian Braun +1
Reverberation negatively impacts the performance of automatic speech recognition (ASR). Prior work on quantifying the effect of reverberation has shown that clarity (C50), a parame…