activity
20202022
most citedInvestigation of Ensemble features of Self-Supervised Pretrained Models for Automatic Speech Recognition

18 citations · 48 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2022★ 18 cited

Investigation of Ensemble features of Self-Supervised Pretrained Models for Automatic Speech Recognition

A Arunkumar, Vrunda N Sukhadia, S. Umesh

Self-supervised learning (SSL) based models have been shown to generate powerful representations that can be used to improve the performance of downstream speech tasks. Several sta…

cs.CL2022

Joint Encoder-Decoder Self-Supervised Pre-training for ASR

Arunkumar A, Umesh S

Self-supervised learning (SSL) has shown tremendous success in various speech-related downstream tasks, including Automatic Speech Recognition (ASR). The output embeddings of the S…

cs.CL2022★ 2 cited

Analyzing the factors affecting usefulness of Self-Supervised Pre-trained Representations for Speech Recognition

Ashish Seth, Lodagala V S V Durga Prasad, Sreyan Ghosh +1

Self-supervised learning (SSL) to learn high-level speech representations has been a popular approach to building Automatic Speech Recognition (ASR) systems in low-resource setting…

cs.CL2022

PADA: Pruning Assisted Domain Adaptation for Self-Supervised Speech Representations

Lodagala V S V Durga Prasad, Sreyan Ghosh, S. Umesh

While self-supervised speech representation learning (SSL) models serve a variety of downstream tasks, these models have been observed to overfit to the domain from which the unlab…

cs.SD2022★ 3 cited

DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation Learning

Sreyan Ghosh, Ashish Seth, and Deepak Mittal +2

Inspired by the recent progress in self-supervised learning for computer vision, in this paper we introduce DeLoRes, a new general-purpose audio representation learning approach. O…

eess.AS2022★ 6 cited

Domain Adaptation of low-resource Target-Domain models using well-trained ASR Conformer Models

Vrunda N. Sukhadia, S. Umesh

In this paper, we investigate domain adaptation for low-resource Automatic Speech Recognition (ASR) of target-domain data, when a well-trained ASR model trained with a large datase…