18 citations · 46 across the 35 of their papers we have counts for
11 papers · 1 filter
Loss Masking Is Not Needed in Decoder-only Transformer for Discrete-token-based ASR
Qian Chen, Wen Wang, Qinglin Zhang +7
Recently, unified speech-text models, such as SpeechGPT, VioLA, and AudioPaLM, have achieved remarkable performance on various speech tasks. These models discretize speech signals…
CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation
Weixiang Yan, Yuchen Tian, Yunzhe Li +2
Recent code translation techniques exploit neural machine translation models to translate source code from one programming language to another to satisfy production compatibility o…
Improving Long Document Topic Segmentation Models With Enhanced Coherence Modeling
Hai Yu, Chong Deng, Qinglin Zhang +3
Topic segmentation is critical for obtaining structured documents and improving downstream tasks such as information retrieval. Due to its ability of automatically exploring clues…
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
Zhihao Du, Jiaming Wang, Qian Chen +12
Generative Pre-trained Transformer (GPT) models have achieved remarkable performance on various natural language processing tasks, and have shown great potential as backbones for a…
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision
Yafeng Chen, Siqi Zheng, Hui Wang +5
Training speaker-discriminative and robust speaker verification systems without explicit speaker labels remains a persistent challenge. In this paper, we propose a novel self-super…
Improving BERT with Hybrid Pooling Network and Drop Mask
Qian Chen, Wen Wang, Qinglin Zhang +3
Transformer-based pre-trained language models, such as BERT, achieve great success in various natural language understanding tasks. Prior research found that BERT captures a rich h…
Advancing Precise Outline-Conditioned Text Generation with Task Duality and Explicit Outline Control
Yunzhe Li, Qian Chen, Weixiang Yan +3
Existing works on outline-conditioned text generation typically aim to generate text using provided outlines as rough sketches, such as keywords and phrases. However, these approac…
Ditto: A Simple and Efficient Approach to Improve Sentence Embeddings
Qian Chen, Wen Wang, Qinglin Zhang +6
Prior studies diagnose the anisotropy problem in sentence representations from pre-trained language models, e.g., BERT, without fine-tuning. Our analysis reveals that the sentence…
Meeting Action Item Detection with Regularized Context Modeling
Jiaqing Liu, Chong Deng, Qinglin Zhang +2
Meetings are increasingly important for collaborations. Action items in meeting transcripts are crucial for managing post-meeting to-do tasks, which usually are summarized laboriou…
MUG: A General Meeting Understanding and Generation Benchmark
Qinglin Zhang, Chong Deng, Jiaqing Liu +7
Listening to long video/audio recordings from video conferencing and online courses for acquiring information is extremely inefficient. Even after ASR systems transcribe recordings…
Overview of the ICASSP 2023 General Meeting Understanding and Generation Challenge (MUG)
Qinglin Zhang, Chong Deng, Jiaqing Liu +7
ICASSP2023 General Meeting Understanding and Generation Challenge (MUG) focuses on prompting a wide range of spoken language processing (SLP) research on meeting transcripts, as SL…