3 citations · 17 across the 16 of their papers we have counts for
9 papers · 1 filter
Listen Again and Choose the Right Answer: A New Paradigm for Automatic Speech Recognition with Large Language Models
Yuchen Hu, Chen Chen, Chengwei Qin +3
Recent advances in large language models (LLMs) have promoted generative error correction (GER) for automatic speech recognition (ASR), which aims to predict the ground-truth trans…
It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition
Chen Chen, Ruizhe Li, Yuchen Hu +4
Recent studies have successfully shown that large language models (LLMs) can be successfully used for generative error correction (GER) on top of the automatic speech recognition (…
GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators
Yuchen Hu, Chen Chen, Chao-Han Huck Yang +4
Recent advances in large language models (LLMs) have stepped forward the development of multilingual speech and machine translation by its reduced representation errors and incorpo…
Large Language Models are Efficient Learners of Noise-Robust Speech Recognition
Yuchen Hu, Chen Chen, Chao-Han Huck Yang +4
Recent advances in large language models (LLMs) have promoted generative error correction (GER) for automatic speech recognition (ASR), which leverages the rich linguistic knowledg…
Affective Decoding for Empathetic Response Generation
Chengkun Zeng, Guanyi Chen, Chenghua Lin +2
Understanding speaker's feelings and producing appropriate responses with emotion connection is a key communicative skill for empathetic dialogue systems. In this paper, we propose…
Improving Variational Autoencoder for Text Modelling with Timestep-Wise Regularisation
Ruizhe Li, Xiao Li, Guanyi Chen +1
The Variational Autoencoder (VAE) is a popular and powerful model applied to text modelling to generate diverse sentences. However, an issue known as posterior collapse (or KL loss…