149 citations · 475 across the 14 of their papers we have counts for
4 papers · 1 filter
Transferring General Multimodal Pretrained Models to Text Recognition
Junyang Lin, Xuancheng Ren, Yichang Zhang +4
This paper proposes a new method, OFA-OCR, to transfer multimodal pretrained models to text recognition. Specifically, we recast text recognition as image captioning and directly t…
OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models
Jinze Bai, Rui Men, Hao Yang +15
Generalist models, which are capable of performing diverse multi-modal tasks in a task-agnostic way within a single model, have been explored recently. Being, hopefully, an alterna…
MMSpeech: Multi-modal Multi-task Encoder-Decoder Pre-training for Speech Recognition
Xiaohuan Zhou, Jiaming Wang, Zeyu Cui +4
In this paper, we propose a novel multi-modal multi-task encoder-decoder pre-training framework (MMSpeech) for Mandarin automatic speech recognition (ASR), which employs both unlab…
Contextual Expressive Text-to-Speech
Jianhong Tu, Zeyu Cui, Xiaohuan Zhou +4
The goal of expressive Text-to-speech (TTS) is to synthesize natural speech with desired content, prosody, emotion, or timbre, in high expressiveness. Most of previous studies atte…