Search Results for author: Zhongqiang Huang

Found 27 papers, 9 papers with code

Adaptive Policy with Wait-$k$ Model for Simultaneous Translation

no code implementations23 Oct 2023 Libo Zhao, Kai Fan, Wei Luo, Jing Wu, Shushu Wang, Ziqian Zeng, Zhongqiang Huang

Simultaneous machine translation (SiMT) requires a robust read/write policy in conjunction with a high-quality translation model.

Machine Translation Translation

BLSP: Bootstrapping Language-Speech Pre-training via Behavior Alignment of Continuation Writing

1 code implementation2 Sep 2023 Chen Wang, Minpeng Liao, Zhongqiang Huang, Jinliang Lu, Junhong Wu, Yuchen Liu, Chengqing Zong, Jiajun Zhang

One is a cascaded approach where outputs (tokens or states) of a separately trained speech recognition system are used as inputs for LLMs, which limits their potential in modeling alignment between speech and text.

speech-recognition Speech Recognition +1

Translate the Beauty in Songs: Jointly Learning to Align Melody and Translate Lyrics

no code implementations28 Mar 2023 Chengxi Li, Kai Fan, Jiajun Bu, Boxing Chen, Zhongqiang Huang, Zhi Yu

Song translation requires both translation of lyrics and alignment of music notes so that the resulting verse can be sung to the accompanying melody, which is a challenging problem that has attracted some interests in different aspects of the translation process.

Decoder Translation

Adapting Offline Speech Translation Models for Streaming with Future-Aware Distillation and Inference

1 code implementation14 Mar 2023 Biao Fu, Minpeng Liao, Kai Fan, Zhongqiang Huang, Boxing Chen, Yidong Chen, Xiaodong Shi

A popular approach to streaming speech translation is to employ a single offline model with a wait-k policy to support different latency requirements, which is simpler than training multiple online models with different latency constraints.

FAD Translation

Entity-to-Text based Data Augmentation for various Named Entity Recognition Tasks

no code implementations19 Oct 2022 Xuming Hu, Yong Jiang, Aiwei Liu, Zhongqiang Huang, Pengjun Xie, Fei Huang, Lijie Wen, Philip S. Yu

Data augmentation techniques have been used to alleviate the problem of scarce labeled data in various NER tasks (flat, nested, and discontinuous NER tasks).

Data Augmentation named-entity-recognition +3

Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation

1 code implementation18 Oct 2022 Chen Wang, Yuchen Liu, Boxing Chen, Jiajun Zhang, Wei Luo, Zhongqiang Huang, Chengqing Zong

Existing zero-shot methods fail to align the two modalities of speech and text into a shared semantic space, resulting in much worse performance compared to the supervised ST methods.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

ITA: Image-Text Alignments for Multi-Modal Named Entity Recognition

1 code implementation NAACL 2022 Xinyu Wang, Min Gui, Yong Jiang, Zixia Jia, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu

As text representations take the most important role in MNER, in this paper, we propose {\bf I}mage-{\bf t}ext {\bf A}lignments (ITA) to align image features into the textual space, so that the attention mechanism in transformer-based pretrained textual embeddings can be better utilized.

Multi-modal Named Entity Recognition named-entity-recognition +1

MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations

1 code implementation EMNLP 2021 Xinyin Ma, Yong Jiang, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Weiming Lu

Entity retrieval, which aims at disambiguating mentions to canonical entities from massive KBs, is essential for many tasks in natural language processing.

Entity Linking Entity Retrieval +1

Multi-View Cross-Lingual Structured Prediction with Minimum Supervision

no code implementations ACL 2021 Zechuan Hu, Yong Jiang, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu

In structured prediction problems, cross-lingual transfer learning is an efficient way to train quality models for low-resource languages, and further improvement can be obtained by learning from multiple source languages.

Cross-Lingual Transfer Sentence +2

Risk Minimization for Zero-shot Sequence Labeling

no code implementations ACL 2021 Zechuan Hu, Yong Jiang, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu

In this paper, we propose a novel unified framework for zero-shot sequence labeling with minimum risk training and design a new decomposable risk function that models the relations between the predicted labels from the source models and the true labels.

Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation

no code implementations AAAI 2021 Ke Wang, Guandan Chen, Zhongqiang Huang, Xiaojun Wan, Fei Huang

Despite the near-human performances already achieved on formal texts such as news articles, neural machine transla- tion still has difficulty in dealing with ”user-generated” texts that have diverse linguistic phenomena but lack large-scale high-quality parallel corpora.

counterfactual Domain Adaptation +2

Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning

3 code implementations ACL 2021 Xinyu Wang, Yong Jiang, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu

We find empirically that the contextual representations computed on the retrieval-based input view, constructed through the concatenation of a sentence and its external contexts, can achieve significantly improved performance compared to the original input view based only on the sentence.

Chinese Named Entity Recognition Chunking +3

Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages

no code implementations23 Feb 2018 Matthew Wiesner, Chunxi Liu, Lucas Ondel, Craig Harman, Vimal Manohar, Jan Trmal, Zhongqiang Huang, Najim Dehak, Sanjeev Khudanpur

Automatic speech recognition (ASR) systems often need to be developed for extremely low-resource languages to serve end-uses such as audio content categorization and search.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Transfer Learning based Dynamic Multiobjective Optimization Algorithms

no code implementations19 Dec 2016 Min Jiang, Zhongqiang Huang, Liming Qiu, Wenzhen Huang, Gary G. Yen

This approach takes the transfer learning method as a tool to help reuse the past experience for speeding up the evolutionary process, and at the same time, any population based multiobjective algorithms can benefit from this integration without any extensive modifications.

BIG-bench Machine Learning Multiobjective Optimization +1

Statistical Machine Translation Features with Multitask Tensor Networks

no code implementations IJCNLP 2015 Hendra Setiawan, Zhongqiang Huang, Jacob Devlin, Thomas Lamar, Rabih Zbib, Richard Schwartz, John Makhoul

We present a three-pronged approach to improving Statistical Machine Translation (SMT), building on recent success in the application of neural networks to SMT.

Machine Translation Tensor Networks +1

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