1 code implementation • 24 Feb 2024 • Chi-Sheng Chen, Guan-Ying Chen, Dong Zhou, Di Jiang, Dai-Shi Chen
Our findings elucidate that our proposed methodology establishes a new benchmark for SOTA performance in food recognition on the CNFOOD-241 dataset.
Ranked #1 on Fine-Grained Image Recognition on CNFOOD-241-Chen
no code implementations • 24 Oct 2023 • Yuanfeng Song, Yuanqin He, Xuefang Zhao, Hanlin Gu, Di Jiang, Haijun Yang, Lixin Fan, Qiang Yang
The springing up of Large Language Models (LLMs) has shifted the community from single-task-orientated natural language processing (NLP) research to a holistic end-to-end multi-task learning paradigm.
no code implementations • 21 Apr 2023 • Yuan Cao, Di Jiang, Guanqun Hou, Fan Deng, Xinjia Chen, Qiang Yang
Face clustering can provide pseudo-labels to the massive unlabeled face data and improve the performance of different face recognition models.
no code implementations • 4 Jan 2022 • Yuanfeng Song, Raymond Chi-Wing Wong, Xuefang Zhao, Di Jiang
We first identify a new task named Speech-to-SQL, which aims to understand the information conveyed by human speech and directly translate it into structured query language (SQL) statements.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • IJCNLP 2019 • Yuanfeng Song, Di Jiang, Weiwei Zhao, Qian Xu, Raymond Chi-Wing Wong, Qiang Yang
With this demonstration, the audience can experience the effect of LMA in an interactive and real-time fashion.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 25 Oct 2019 • Yuanfeng Song, Di Jiang, Xuefang Zhao, Qian Xu, Raymond Chi-Wing Wong, Lixin Fan, Qiang Yang
Modern Automatic Speech Recognition (ASR) systems primarily rely on scores from an Acoustic Model (AM) and a Language Model (LM) to rescore the N-best lists.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • WS 2019 • Shaobo Cui, Rongzhong Lian, Di Jiang, Yuanfeng Song, Siqi Bao, Yong Jiang
DAL is the first work to innovatively utilizes the duality between query generation and response generation to avoid safe responses and increase the diversity of the generated responses.
1 code implementation • 11 Aug 2018 • Di Jiang, Yuanfeng Song, Rongzhong Lian, Siqi Bao, Jinhua Peng, Huang He, Hua Wu
In order to relieve burdens of software engineers without knowledge of Bayesian networks, Familia is able to conduct automatic parameter inference for a variety of topic models.
1 code implementation • 31 Jul 2017 • Di Jiang, Zeyu Chen, Rongzhong Lian, Siqi Bao, Chen Li
Familia is an open-source toolkit for pragmatic topic modeling in industry.
no code implementations • COLING 2016 • Di Jiang, Lei Shi, Rongzhong Lian, Hua Wu
Topic modeling and word embedding are two important techniques for deriving latent semantics from data.