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20182026
most citedImproving Transformer-based Speech Recognition Using Unsupervised Pre-training

102 citations · 112 across the 11 of their papers we have counts for

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9 papers · 1 filter

cs.CL2025

Understanding the Modality Gap: An Empirical Study on the Speech-Text Alignment Mechanism of Large Speech Language Models

Bajian Xiang, Shuaijiang Zhao, Tingwei Guo +1

End-to-end Large Speech Language Models (LSLMs) have demonstrated impressive conversational generation abilities, yet consistently fall short of traditional pipeline systems on sem…

cs.CL2025

SARI: Structured Audio Reasoning via Curriculum-Guided Reinforcement Learning

Cheng Wen, Tingwei Guo, Shuaijiang Zhao +2

Recent work shows that reinforcement learning(RL) can markedly sharpen the reasoning ability of large language models (LLMs) by prompting them to "think before answering." Yet whet…

cs.CL20241 cited

Advancing Speech Language Models by Scaling Supervised Fine-Tuning with Over 60,000 Hours of Synthetic Speech Dialogue Data

Shuaijiang Zhao, Tingwei Guo, Bajian Xiang +4

The GPT-4o represents a significant milestone in enabling real-time interaction with large language models (LLMs) through speech, its remarkable low latency and high fluency not on…

cs.CL2020

TMT: A Transformer-based Modal Translator for Improving Multimodal Sequence Representations in Audio Visual Scene-aware Dialog

Wubo Li, Dongwei Jiang, Wei Zou +1

Audio Visual Scene-aware Dialog (AVSD) is a task to generate responses when discussing about a given video. The previous state-of-the-art model shows superior performance for this…

cs.CL2020

Speech SIMCLR: Combining Contrastive and Reconstruction Objective for Self-supervised Speech Representation Learning

Dongwei Jiang, Wubo Li, Miao Cao +2

Self-supervised visual pretraining has shown significant progress recently. Among those methods, SimCLR greatly advanced the state of the art in self-supervised and semi-supervised…

cs.CL2019102 cited

Improving Transformer-based Speech Recognition Using Unsupervised Pre-training

Dongwei Jiang, Xiaoning Lei, Wubo Li +4

Speech recognition technologies are gaining enormous popularity in various industrial applications. However, building a good speech recognition system usually requires large amount…