86 citations · 278 across the 36 of their papers we have counts for
20 papers · 1 filter
Adapting Personalized Speech Enhancement for Low-Latency Audio-Visual Target-Speaker Extraction
Rayhan Rashed, Senja Filipi, Ross Cutler
Online audio-visual target-speaker extraction aims to remove competing voices while preserving speech quality and bounding lookahead. Existing extractors are built and evaluated fo…
Improving Meeting Inclusiveness using Speech Interruption Analysis
Szu-Wei Fu, Yaran Fan, Yasaman Hosseinkashi +2
Meetings are a pervasive method of communication within all types of companies and organizations, and using remote collaboration systems to conduct meetings has increased dramatica…
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…
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…
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…
Aura: Privacy-preserving Augmentation to Improve Test Set Diversity in Speech Enhancement
Xavier Gitiaux, Aditya Khant, Ebrahim Beyrami +3
Noise suppression models running in production environments are commonly trained on publicly available datasets. However, this approach leads to regressions due to the lack of trai…
MusicNet: Compact Convolutional Neural Network for Real-time Background Music Detection
Chandan K. A. Reddy, Vishak Gopa, Harishchandra Dubey +3
With the recent growth of remote work, online meetings often encounter challenging audio contexts such as background noise, music, and echo. Accurate real-time detection of music e…
AECMOS: A speech quality assessment metric for echo impairment
Marju Purin, Sten Sootla, Mateja Sponza +2
Traditionally, the quality of acoustic echo cancellers is evaluated using intrusive speech quality assessment measures such as ERLE \cite{g168} and PESQ \cite{p862}, or by carrying…
DNSMOS P.835: A Non-Intrusive Perceptual Objective Speech Quality Metric to Evaluate Noise Suppressors
Chandan K A Reddy, Vishak Gopal, Ross Cutler
Human subjective evaluation is the gold standard to evaluate speech quality optimized for human perception. Perceptual objective metrics serve as a proxy for subjective scores. We…
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…
Subjective Evaluation of Noise Suppression Algorithms in Crowdsourcing
Babak Naderi, Ross Cutler
The quality of the speech communication systems, which include noise suppression algorithms, are typically evaluated in laboratory experiments according to the ITU-T Rec. P.835, in…
Crowdsourcing approach for subjective evaluation of echo impairment
Ross Cutler, Babak Naderi, Markus Loide +2
The quality of acoustic echo cancellers (AECs) in real-time communication systems is typically evaluated using objective metrics like ERLE and PESQ, and less commonly with lab-base…
DNN No-Reference PSTN Speech Quality Prediction
Gabriel Mittag, Ross Cutler, Yasaman Hosseinkashi +4
Classic public switched telephone networks (PSTN) are often a black box for VoIP network providers, as they have no access to performance indicators, such as delay or packet loss.…
An Open source Implementation of ITU-T Recommendation P.808 with Validation
Babak Naderi, Ross Cutler
The ITU-T Recommendation P.808 provides a crowdsourcing approach for conducting a subjective assessment of speech quality using the Absolute Category Rating (ACR) method. We provid…
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…
Multimodal active speaker detection and virtual cinematography for video conferencing
Ross Cutler, Ramin Mehran, Sam Johnson +4
Active speaker detection (ASD) and virtual cinematography (VC) can significantly improve the remote user experience of a video conference by automatically panning, tilting and zoom…
Non-intrusive speech quality assessment using neural networks
Anderson R. Avila, Hannes Gamper, Chandan Reddy +3
Estimating the perceived quality of an audio signal is critical for many multimedia and audio processing systems. Providers strive to offer optimal and reliable services in order t…