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20242026
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eess.AS2025

Frozen Large Language Models Can Perceive Paralinguistic Aspects of Speech

Wonjune Kang, Junteng Jia, Chunyang Wu +8

This work studies the capabilities of a large language model (LLM) to understand paralinguistic aspects of speech without fine-tuning its weights. We utilize an end-to-end system w…

eess.AS2024

CJST: CTC Compressor based Joint Speech and Text Training for Decoder-Only ASR

Wei Zhou, Junteng Jia, Leda Sari +2

CTC compressor can be an effective approach to integrate audio encoders to decoder-only models, which has gained growing interest for different speech applications. In this work, w…

eess.AS2024

M-BEST-RQ: A Multi-Channel Speech Foundation Model for Smart Glasses

Yufeng Yang, Desh Raj, Ju Lin +8

The growing popularity of multi-channel wearable devices, such as smart glasses, has led to a surge of applications such as targeted speech recognition and enhanced hearing. Howeve…

eess.AS2024

Faster Speech-LLaMA Inference with Multi-token Prediction

Desh Raj, Gil Keren, Junteng Jia +2

Large language models (LLMs) have become proficient at solving a wide variety of tasks, including those involving multi-modal inputs. In particular, instantiating an LLM (such as L…

eess.AS2024

Effective internal language model training and fusion for factorized transducer model

Jinxi Guo, Niko Moritz, Yingyi Ma +6

The internal language model (ILM) of the neural transducer has been widely studied. In most prior work, it is mainly used for estimating the ILM score and is subsequently subtracte…