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20222026
most citedFrozen Large Language Models Can Perceive Paralinguistic Aspects of Speech

6 citations · 15 across the 20 of their papers we have counts for

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eess.AS2024

Textless Streaming Speech-to-Speech Translation using Semantic Speech Tokens

Jinzheng Zhao, Niko Moritz, Egor Lakomkin +7

Cascaded speech-to-speech translation systems often suffer from the error accumulation problem and high latency, which is a result of cascaded modules whose inference delays accumu…

eess.AS2024★ 6 cited

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

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.AS2023

End-to-End Speech Recognition Contextualization with Large Language Models

Egor Lakomkin, Chunyang Wu, Yassir Fathullah +3

In recent years, Large Language Models (LLMs) have garnered significant attention from the research community due to their exceptional performance and generalization capabilities.…

eess.AS2023★ 2 cited

Prompting Large Language Models with Speech Recognition Abilities

Yassir Fathullah, Chunyang Wu, Egor Lakomkin +9

Large language models have proven themselves highly flexible, able to solve a wide range of generative tasks, such as abstractive summarization and open-ended question answering. I…