68 citations · 180 across the 16 of their papers we have counts for
11 papers · 1 filter
A Comparison of Deep Learning MOS Predictors for Speech Synthesis Quality
Alessandro Ragano, Emmanouil Benetos, Michael Chinen +4
Speech synthesis quality prediction has made remarkable progress with the development of supervised and self-supervised learning (SSL) MOS predictors but some aspects related to th…
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…
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…
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…
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…
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…
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…
Noise dependent Super Gaussian-Coherence based dual microphone Speech Enhancement for hearing aid application using smartphone
Nikhil Shankar, Gautam S Bhat, Chandan K A Reddy +1
In this paper, the coherence between speech and noise signals is used to obtain a Speech Enhancement (SE) gain function, in combination with a Super Gaussian Joint Maximum a Poster…
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…