102 citations · 169 across the 8 of their papers we have counts for
8 papers
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…
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…
DiDiSpeech: A Large Scale Mandarin Speech Corpus
Tingwei Guo, Cheng Wen, Dongwei Jiang +8
This paper introduces a new open-sourced Mandarin speech corpus, called DiDiSpeech. It consists of about 800 hours of speech data at 48kHz sampling rate from 6000 speakers and the…
Transformer based unsupervised pre-training for acoustic representation learning
Ruixiong Zhang, Haiwei Wu, Wubo Li +3
Recently, a variety of acoustic tasks and related applications arised. For many acoustic tasks, the labeled data size may be limited. To handle this problem, we propose an unsuperv…
A Further Study of Unsupervised Pre-training for Transformer Based Speech Recognition
Dongwei Jiang, Wubo Li, Ruixiong Zhang +5
Building a good speech recognition system usually requires large amounts of transcribed data, which is expensive to collect. To tackle this problem, many unsupervised pre-training…
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…
TCT: A Cross-supervised Learning Method for Multimodal Sequence Representation
Wubo Li, Wei Zou, Xiangang Li
Multimodalities provide promising performance than unimodality in most tasks. However, learning the semantic of the representations from multimodalities efficiently is extremely ch…
A Multi-Modal Chinese Poetry Generation Model
Dayiheng Liu, Quan Guo, Wubo Li +1
Recent studies in sequence-to-sequence learning demonstrate that RNN encoder-decoder structure can successfully generate Chinese poetry. However, existing methods can only generate…