11 citations · 21 across the 7 of their papers we have counts for
7 papers
A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data
Minh Tran, Yutong Pang, Debjyoti Paul +7
We introduce DAS (Domain Adaptation with Synthetic data), a novel domain adaptation framework for pre-trained ASR model, designed to efficiently adapt to various language-defined d…
LLaMA based Punctuation Restoration With Forward Pass Only Decoding
Yutong Pang, Debjyoti Paul, Kevin Jiang +2
This paper introduces two advancements in the field of Large Language Model Annotation with a focus on punctuation restoration tasks. Our first contribution is the application of L…
Towards scalable efficient on-device ASR with transfer learning
Laxmi Pandey, Ke Li, Jinxi Guo +4
Multilingual pretraining for transfer learning significantly boosts the robustness of low-resource monolingual ASR models. This study systematically investigates three main aspects…
SignDiff: Diffusion Model for American Sign Language Production
Sen Fang, Chunyu Sui, Yanghao Zhou +4
In this paper, we propose a dual-condition diffusion pre-training model named SignDiff that can generate human sign language speakers from a skeleton pose. SignDiff has a novel Fra…
Language Agnostic Data-Driven Inverse Text Normalization
Szu-Jui Chen, Debjyoti Paul, Yutong Pang +2
With the emergence of automatic speech recognition (ASR) models, converting the spoken form text (from ASR) to the written form is in urgent need. This inverse text normalization (…
Improving Data Driven Inverse Text Normalization using Data Augmentation
Laxmi Pandey, Debjyoti Paul, Pooja Chitkara +6
Inverse text normalization (ITN) is used to convert the spoken form output of an automatic speech recognition (ASR) system to a written form. Traditional handcrafted ITN rules can…
Speech recognition for medical conversations
Chung-Cheng Chiu, Anshuman Tripathi, Katherine Chou +11
In this work we explored building automatic speech recognition models for transcribing doctor patient conversation. We collected a large scale dataset of clinical conversations ($1…