Search Results for author: Vishak Gopal

Found 8 papers, 2 papers with code

Performance optimizations on deep noise suppression models

no code implementations8 Oct 2021 Jerry Chee, Sebastian Braun, Vishak Gopal, Ross Cutler

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.

Speech Quality

DNSMOS P.835: A Non-Intrusive Perceptual Objective Speech Quality Metric to Evaluate Noise Suppressors

no code implementations5 Oct 2021 Chandan K A Reddy, Vishak Gopal, Ross Cutler

In this work, we train an objective metric based on P. 835 human ratings that outputs 3 scores: i) speech quality (SIG), ii) background noise quality (BAK), and iii) the overall quality (OVRL) of the audio.

Speech Quality

Interspeech 2021 Deep Noise Suppression Challenge

1 code implementation6 Jan 2021 Chandan K A Reddy, Harishchandra Dubey, Kazuhito Koishida, Arun Nair, Vishak Gopal, Ross Cutler, Sebastian Braun, Hannes Gamper, Robert Aichner, Sriram Srinivasan

In this version of the challenge organized at INTERSPEECH 2021, we are expanding both our training and test datasets to accommodate full band scenarios.

Denoising Speech Quality

DNSMOS: A Non-Intrusive Perceptual Objective Speech Quality metric to evaluate Noise Suppressors

no code implementations28 Oct 2020 Chandan K A Reddy, Vishak Gopal, Ross Cutler

The no-reference approaches correlate poorly with human ratings and are not widely adopted in the research community.

Speech Quality

The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results

no code implementations16 May 2020 Chandan K. A. Reddy, Vishak Gopal, Ross Cutler, Ebrahim Beyrami, Roger Cheng, Harishchandra Dubey, Sergiy Matusevych, Robert Aichner, Ashkan Aazami, Sebastian Braun, Puneet Rana, Sriram Srinivasan, Johannes Gehrke

In this challenge, we open-sourced a large clean speech and noise corpus for training the noise suppression models and a representative test set to real-world scenarios consisting of both synthetic and real recordings.

Speech Enhancement

The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework

no code implementations23 Jan 2020 Chandan K. A. Reddy, Ebrahim Beyrami, Harishchandra Dubey, Vishak Gopal, Roger Cheng, Ross Cutler, Sergiy Matusevych, Robert Aichner, Ashkan Aazami, Sebastian Braun, Puneet Rana, Sriram Srinivasan, Johannes Gehrke

In this challenge, we open-source a large clean speech and noise corpus for training the noise suppression models and a representative test set to real-world scenarios consisting of both synthetic and real recordings.

Speech Enhancement Speech Quality

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