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eess.AS2026
Can LLMs Help Localize Fake Words in Partially Fake Speech?
Lin Zhang, Thomas Thebaud, Zexin Cai +5
Large language models (LLMs), trained on large-scale text, have recently attracted significant attention for their strong performance across many tasks. Motivated by this, we inves…
eess.AS2024
Improving Neural Biasing for Contextual Speech Recognition by Early Context Injection and Text Perturbation
Ruizhe Huang, Mahsa Yarmohammadi, Sanjeev Khudanpur +1
Existing research suggests that automatic speech recognition (ASR) models can benefit from additional contexts (e.g., contact lists, user specified vocabulary). Rare words and name…
eess.AS2024
Multi-Channel Multi-Speaker ASR Using Target Speaker's Solo Segment
Yiwen Shao, Shi-Xiong Zhang, Yong Xu +4
In the field of multi-channel, multi-speaker Automatic Speech Recognition (ASR), the task of discerning and accurately transcribing a target speaker's speech within background nois…