3 citations · 9 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…
Contextual Biasing of Named-Entities with Large Language Models
Chuanneng Sun, Zeeshan Ahmed, Yingyi Ma +4
This paper studies contextual biasing with Large Language Models (LLMs), where during second-pass rescoring additional contextual information is provided to a LLM to boost Automati…
Recovering from Privacy-Preserving Masking with Large Language Models
Arpita Vats, Zhe Liu, Peng Su +5
Model adaptation is crucial to handle the discrepancy between proxy training data and actual users data received. To effectively perform adaptation, textual data of users is typica…
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…
Improving N-gram Language Models with Pre-trained Deep Transformer
Yiren Wang, Hongzhao Huang, Zhe Liu +4
Although n-gram language models (LMs) have been outperformed by the state-of-the-art neural LMs, they are still widely used in speech recognition due to its high efficiency in infe…