18 citations · 27 across the 7 of their papers we have counts for
9 papers
HARNESS: Lightweight Distilled Arabic Speech Foundation Models
Vrunda N. Sukhadia, Shammur Absar Chowdhury
Large self-supervised speech (SSL) models achieve strong downstream performance, but their size limits deployment in resource-constrained settings. We present HArnESS, an Arabic-ce…
HARNESS: Lightweight Distilled Arabic Speech Foundation Models
Vrunda N. sukhadia, Shammur Absar Chowdhury
Large pre-trained speech models excel in downstream tasks but their deployment is impractical for resource-limited environments. In this paper, we introduce HArnESS, the first Arab…
NativQA: Multilingual Culturally-Aligned Natural Query for LLMs
Md. Arid Hasan, Maram Hasanain, Fatema Ahmad +6
Natural Question Answering (QA) datasets play a crucial role in evaluating the capabilities of large language models (LLMs), ensuring their effectiveness in real-world applications…
Children's Speech Recognition through Discrete Token Enhancement
Vrunda N. Sukhadia, Shammur Absar Chowdhury
Children's speech recognition is considered a low-resource task mainly due to the lack of publicly available data. There are several reasons for such data scarcity, including expen…
The Tag-Team Approach: Leveraging CLS and Language Tagging for Enhancing Multilingual ASR
Kaousheik Jayakumar, Vrunda N. Sukhadia, A Arunkumar +1
Building a multilingual Automated Speech Recognition (ASR) system in a linguistically diverse country like India can be a challenging task due to the differences in scripts and the…
Channel-Aware Pretraining of Joint Encoder-Decoder Self-Supervised Model for Telephonic-Speech ASR
Vrunda N. Sukhadia, A. Arunkumar, S. Umesh
This paper proposes a novel technique to obtain better downstream ASR performance from a joint encoder-decoder self-supervised model when trained with speech pooled from two differ…
Technology Pipeline for Large Scale Cross-Lingual Dubbing of Lecture Videos into Multiple Indian Languages
Anusha Prakash, Arun Kumar, Ashish Seth +24
Cross-lingual dubbing of lecture videos requires the transcription of the original audio, correction and removal of disfluencies, domain term discovery, text-to-text translation in…
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…
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…