2 citations · 3 across the 4 of their papers we have counts for
4 papers
Speech Token Prediction via Compressed-to-fine Language Modeling for Speech Generation
Wenrui Liu, Qian Chen, Wen Wang +11
Neural audio codecs, used as speech tokenizers, have demonstrated remarkable potential in the field of speech generation. However, to ensure high-fidelity audio reconstruction, neu…
WavChat: A Survey of Spoken Dialogue Models
Shengpeng Ji, Yifu Chen, Minghui Fang +16
Recent advancements in spoken dialogue models, exemplified by systems like GPT-4o, have captured significant attention in the speech domain. Compared to traditional three-tier casc…
Analyzing and Mitigating Inconsistency in Discrete Audio Tokens for Neural Codec Language Models
Wenrui Liu, Zhifang Guo, Jin Xu +4
Building upon advancements in Large Language Models (LLMs), the field of audio processing has seen increased interest in training audio generation tasks with discrete audio token s…
Leveraging Annotator Disagreement for Text Classification
Jin Xu, Mariët Theune, Daniel Braun
It is common practice in text classification to only use one majority label for model training even if a dataset has been annotated by multiple annotators. Doing so can remove valu…