65 citations · 88 across the 6 of their papers we have counts for
6 papers
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…
Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications
Jamie Pool, Ebrahim Beyrami, Vishak Gopal +7
Web-scale applications can ship code on a daily to weekly cadence. These applications rely on online metrics to monitor the health of new releases. Regressions in metric values nee…
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…
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…
A scalable noisy speech dataset and online subjective test framework
Chandan K. A. Reddy, Ebrahim Beyrami, Jamie Pool +3
Background noise is a major source of quality impairments in Voice over Internet Protocol (VoIP) and Public Switched Telephone Network (PSTN) calls. Recent work shows the efficacy…
On Design of Problem Token Questions in Quality of Experience Surveys
Jayant Gupchup, Ebrahim Beyrami, Martin Ellis +3
User surveys for Quality of Experience (QoE) are a critical source of information. In addition to the common "star rating" used to estimate Mean Opinion Score (MOS), more detailed…