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20232026
most citedPrompting Large Language Models for Zero-Shot Domain Adaptation in Speech Recognition

2 citations · 5 across the 16 of their papers we have counts for

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5 papers · 1 filter

cs.AI2023

A Multitask Training Approach to Enhance Whisper with Contextual Biasing and Open-Vocabulary Keyword Spotting

Yuang Li, Min Zhang, Chang Su +7

The recognition of rare named entities, such as personal names and terminologies, is challenging for automatic speech recognition (ASR) systems, especially when they are not freque…

cs.CL2023

Accelerating Transducers through Adjacent Token Merging

Yuang Li, Yu Wu, Jinyu Li +1

Recent end-to-end automatic speech recognition (ASR) systems often utilize a Transformer-based acoustic encoder that generates embedding at a high frame rate. However, this design…

cs.CL2023★ 2 cited

Prompting Large Language Models for Zero-Shot Domain Adaptation in Speech Recognition

Yuang Li, Yu Wu, Jinyu Li +1

The integration of Language Models (LMs) has proven to be an effective way to address domain shifts in speech recognition. However, these approaches usually require a significant a…

cs.CL2023

Accurate and Structured Pruning for Efficient Automatic Speech Recognition

Huiqiang Jiang, Li Lyna Zhang, Yuang Li +7

Automatic Speech Recognition (ASR) has seen remarkable advancements with deep neural networks, such as Transformer and Conformer. However, these models typically have large model s…

eess.AS2023★ 1 cited

Self-Supervised Learning-Based Source Separation for Meeting Data

Yuang Li, Xianrui Zheng, Philip C. Woodland

Source separation can improve automatic speech recognition (ASR) under multi-party meeting scenarios by extracting single-speaker signals from overlapped speech. Despite the succes…