6 citations · 7 across the 10 of their papers we have counts for
10 papers
Gender Bias in MT for a Genderless Language: New Benchmarks for Basque
Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez
Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…
Can Speech LLMs Think while Listening?
Yi-Jen Shih, Desh Raj, Chunyang Wu +6
Recent advances in speech large language models (speech LLMs) have enabled seamless spoken interactions, but these systems still struggle with complex reasoning tasks. Previously,…
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,…
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…
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…
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…
AudioChatLlama: Towards General-Purpose Speech Abilities for LLMs
Yassir Fathullah, Chunyang Wu, Egor Lakomkin +7
In this work, we extend the instruction-tuned Llama-2 model with end-to-end general-purpose speech processing and reasoning abilities while maintaining the wide range of original L…
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.…
Dynamic ASR Pathways: An Adaptive Masking Approach Towards Efficient Pruning of A Multilingual ASR Model
Jiamin Xie, Ke Li, Jinxi Guo +7
Neural network pruning offers an effective method for compressing a multilingual automatic speech recognition (ASR) model with minimal performance loss. However, it entails several…
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models
Yuan Shangguan, Haichuan Yang, Danni Li +11
Automatic Speech Recognition (ASR) models need to be optimized for specific hardware before they can be deployed on devices. This can be done by tuning the model's hyperparameters…