1 code implementation • 27 Feb 2022 • Harishchandra Dubey, Vishak Gopal, Ross Cutler, Ashkan Aazami, Sergiy Matusevych, Sebastian Braun, Sefik Emre Eskimez, Manthan Thakker, Takuya Yoshioka, Hannes Gamper, Robert Aichner
We open-source datasets and test sets for researchers to train their deep noise suppression models, as well as a subjective evaluation framework based on ITU-T P. 835 to rate and rank-order the challenge entries.
no code implementations • 8 Oct 2021 • Chandan K. A. Reddy, Vishak Gopa, Harishchandra Dubey, Sergiy Matusevych, Ross Cutler, Robert Aichner
With the recent growth of remote work, online meetings often encounter challenging audio contexts such as background noise, music, and echo.
2 code implementations • 6 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.
1 code implementation • 16 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.
1 code implementation • 23 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.
no code implementations • 12 Jan 2020 • Harishchandra Dubey, Dimitra Emmanouilidou, Ivan J. Tashev
While Ladder network is robust to data mismatches, simpler SVM and ELM classifiers are sensitive to such mismatches, where the proposed normalization techniques can play an important role.
no code implementations • 19 Aug 2019 • Debanjan Borthakur, Victoria Grace, Paul Batchelor, Harishchandra Dubey, Kunal Mankodiya
This work explores the use of auditory display in aiding the analysis of HRV leveraged by unsupervised machine learning techniques.
no code implementations • 12 Jul 2019 • Harishchandra Dubey, Abhijeet Sangwan, John Hansen
Relative reduction in diarization error rate (DER) for CRSS-PLTL corpus is 43. 22% using the proposed advancements as compared to baseline.
no code implementations • 1 Oct 2016 • Shiba R. Paital, Prakash K. Ray, Asit Mohanty, Sandipan Patra, Harishchandra Dubey
The performance of STATCOM with the above soft-computing techniques are studied and compared with the conventional PID controller under various scenarios.
no code implementations • 30 May 2016 • Harishchandra Dubey, Nandita, Ashutosh Kumar Tiwari
In this work, a pattern recognition system is investigated for blind automatic classification of digitally modulated communication signals.
no code implementations • 30 May 2016 • Harishchandra Dubey, A. K. Tiwari, Nandita, P. K. Ray, S. R. Mohanty, Nand Kishor
This paper presents a novel approach for fault classification and section identification in a series compensated transmission line based on least square support vector machine.