no code implementations • 1 Jun 2023 • Sameer Khurana, Nauman Dawalatabad, Antoine Laurent, Luis Vicente, Pablo Gimeno, Victoria Mingote, James Glass
Having a single model that supports multiple translation tasks is desirable.
no code implementations • 14 Nov 2022 • Nauman Dawalatabad, Sameer Khurana, Antoine Laurent, James Glass
Dropout-based Uncertainty-driven Self-Training (DUST) proceeds by first training a teacher model on source domain labeled data.
no code implementations • 1 Oct 2022 • Jash Rathod, Nauman Dawalatabad, Shatrughan Singh, Dhananjaya Gowda
Knowledge distillation (KD) is a popular model compression approach that has shown to achieve smaller model size with relatively lesser degradation in the model performance.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 8 Jan 2022 • Nauman Dawalatabad, Tushar Vatsal, Ashutosh Gupta, Sungsoo Kim, Shatrughan Singh, Dhananjaya Gowda, Chanwoo Kim
With the use of popular transducer-based models, it has become possible to practically deploy streaming speech recognition models on small devices .
4 code implementations • 8 Jun 2021 • Mirco Ravanelli, Titouan Parcollet, Peter Plantinga, Aku Rouhe, Samuele Cornell, Loren Lugosch, Cem Subakan, Nauman Dawalatabad, Abdelwahab Heba, Jianyuan Zhong, Ju-chieh Chou, Sung-Lin Yeh, Szu-Wei Fu, Chien-Feng Liao, Elena Rastorgueva, François Grondin, William Aris, Hwidong Na, Yan Gao, Renato de Mori, Yoshua Bengio
SpeechBrain is an open-source and all-in-one speech toolkit.
no code implementations • 3 Apr 2021 • Nauman Dawalatabad, Mirco Ravanelli, François Grondin, Jenthe Thienpondt, Brecht Desplanques, Hwidong Na
Learning robust speaker embeddings is a crucial step in speaker diarization.
no code implementations • 4 Mar 2021 • Nauman Dawalatabad, Jilt Sebastian, Jom Kuriakose, C. Chandra Sekhar, Shrikanth Narayanan, Hema A. Murthy
In this work, we address the problem of separating the percussive voices in the taniavartanam segments of Carnatic music.