18 citations · 48 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
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…
DECAR: Deep Clustering for learning general-purpose Audio Representations
Sreyan Ghosh, Sandesh V Katta, Ashish Seth +1
We introduce DECAR, a self-supervised pre-training approach for learning general-purpose audio representations. Our system is based on clustering: it utilizes an offline clustering…
S-vectors and TESA: Speaker Embeddings and a Speaker Authenticator Based on Transformer Encoder
N J Metilda Sagaya Mary, S Umesh, Sandesh V Katta
One of the most popular speaker embeddings is x-vectors, which are obtained from an architecture that gradually builds a larger temporal context with layers. In this paper, we prop…
Investigation of Speaker-adaptation methods in Transformer based ASR
Vishwas M. Shetty, Metilda Sagaya Mary N J, S. Umesh
End-to-end models are fast replacing the conventional hybrid models in automatic speech recognition. Transformer, a sequence-to-sequence model, based on self-attention popularly us…
Modified SPLICE and its Extension to Non-Stereo Data for Noise Robust Speech Recognition
D. S. Pavan Kumar, N. Vishnu Prasad, Vikas Joshi +1
In this paper, a modification to the training process of the popular SPLICE algorithm has been proposed for noise robust speech recognition. The modification is based on feature co…