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20232026
most citedFrozen Large Language Models Can Perceive Paralinguistic Aspects of Speech

6 citations · 7 across the 14 of their papers we have counts for

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7 papers · 1 filter

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…

cs.CL2024

LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch

Jan Pfister, Julia Wunderle, Andreas Hotho

We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…

cs.SD2024

Efficient Streaming LLM for Speech Recognition

Junteng Jia, Gil Keren, Wei Zhou +6

Recent works have shown that prompting large language models with audio encodings can unlock speech recognition capabilities. However, existing techniques do not scale efficiently,…

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.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…

cs.CL2024★ 1 cited

Speech ReaLLM -- Real-time Streaming Speech Recognition with Multimodal LLMs by Teaching the Flow of Time

Frank Seide, Morrie Doulaty, Yangyang Shi +3

We introduce Speech ReaLLM, a new ASR architecture that marries "decoder-only" ASR with the RNN-T to make multimodal LLM architectures capable of real-time streaming. This is the f…