17 citations · 49 across the 24 of their papers we have counts for
5 papers · 1 filter
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…
3D-Speaker: A Large-Scale Multi-Device, Multi-Distance, and Multi-Dialect Corpus for Speech Representation Disentanglement
Siqi Zheng, Luyao Cheng, Yafeng Chen +2
Disentangling uncorrelated information in speech utterances is a crucial research topic within speech community. Different speech-related tasks focus on extracting distinct speech…
Exploring Speaker-Related Information in Spoken Language Understanding for Better Speaker Diarization
Luyao Cheng, Siqi Zheng, Zhang Qinglin +3
Speaker diarization(SD) is a classic task in speech processing and is crucial in multi-party scenarios such as meetings and conversations. Current mainstream speaker diarization ap…
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…
PoNet: Pooling Network for Efficient Token Mixing in Long Sequences
Chao-Hong Tan, Qian Chen, Wen Wang +3
Transformer-based models have achieved great success in various NLP, vision, and speech tasks. However, the core of Transformer, the self-attention mechanism, has a quadratic time…