activity
20162022
most citedFog Computing in Medical Internet-of-Things: Architecture, Implementation, and Applications

65 citations · 138 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.SD2021

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…

cs.SD2020

CURE Dataset: Ladder Networks for Audio Event Classification

Harishchandra Dubey, Dimitra Emmanouilidou, Ivan J. Tashev

Audio event classification is an important task for several applications such as surveillance, audio, video and multimedia retrieval etc. There are approximately 3M people with hea…

cs.SD2020

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…

cs.SD2019

Toeplitz Inverse Covariance based Robust Speaker Clustering for Naturalistic Audio Streams

Harishchandra Dubey, Abhijeet Sangwan, John Hansen

Speaker diarization determines who spoke and when? in an audio stream. In this study, we propose a model-based approach for robust speaker clustering using i-vectors. The ivectors…

cs.SD2018

Robust Speaker Clustering using Mixtures of von Mises-Fisher Distributions for Naturalistic Audio Streams

Harishchandra Dubey, Abhijeet Sangwan, John H. L. Hansen

Speaker Diarization (i.e. determining who spoke and when?) for multi-speaker naturalistic interactions such as Peer-Led Team Learning (PLTL) sessions is a challenging task. In this…

cs.SD2018

Robust Feature Clustering for Unsupervised Speech Activity Detection

Harishchandra Dubey, Abhijeet Sangwan, John H. L. Hansen

In certain applications such as zero-resource speech processing or very-low resource speech-language systems, it might not be feasible to collect speech activity detection (SAD) an…