2 code implementations • 7 Nov 2022 • Xiaoran Fan, Chao Pang, Tian Yuan, He Bai, Renjie Zheng, Pengfei Zhu, Shuohuan Wang, Junkun Chen, Zeyu Chen, Liang Huang, Yu Sun, Hua Wu
In this paper, we extend the pretraining method for cross-lingual multi-speaker speech synthesis tasks, including cross-lingual multi-speaker voice cloning and cross-lingual multi-speaker speech editing.
2 code implementations • NAACL (ACL) 2022 • HUI ZHANG, Tian Yuan, Junkun Chen, Xintong Li, Renjie Zheng, Yuxin Huang, Xiaojie Chen, Enlei Gong, Zeyu Chen, Xiaoguang Hu, dianhai yu, Yanjun Ma, Liang Huang
PaddleSpeech is an open-source all-in-one speech toolkit.
Automatic Speech Recognition (ASR) Environmental Sound Classification +9
no code implementations • 27 Apr 2022 • Guangxu Xun, Mingbo Ma, Yuchen Bian, Xingyu Cai, Jiaji Huang, Renjie Zheng, Junkun Chen, Jiahong Yuan, Kenneth Church, Liang Huang
In simultaneous translation (SimulMT), the most widely used strategy is the wait-k policy thanks to its simplicity and effectiveness in balancing translation quality and latency.
2 code implementations • 18 Mar 2022 • He Bai, Renjie Zheng, Junkun Chen, Xintong Li, Mingbo Ma, Liang Huang
Recently, speech representation learning has improved many speech-related tasks such as speech recognition, speech classification, and speech-to-text translation.
no code implementations • 2 Aug 2021 • Jiahong Yuan, Xingyu Cai, Dongji Gao, Renjie Zheng, Liang Huang, Kenneth Church
Much of the recent literature on automatic speech recognition (ASR) is taking an end-to-end approach.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 2 Aug 2021 • Jiahong Yuan, Xingyu Cai, Renjie Zheng, Liang Huang, Kenneth Church
Models of phonemes, broad phonetic classes, and syllables all significantly outperform the utterance model, demonstrating that phonetic units are helpful and should be incorporated in speech emotion recognition.
no code implementations • Findings (ACL) 2021 • Junkun Chen, Mingbo Ma, Renjie Zheng, Liang Huang
Simultaneous speech-to-text translation is widely useful in many scenarios.
no code implementations • 10 Feb 2021 • Renjie Zheng, Junkun Chen, Mingbo Ma, Liang Huang
Recently, representation learning for text and speech has successfully improved many language related tasks.
no code implementations • 22 Oct 2020 • Junkun Chen, Mingbo Ma, Renjie Zheng, Liang Huang
End-to-end Speech-to-text Translation (E2E-ST), which directly translates source language speech to target language text, is widely useful in practice, but traditional cascaded approaches (ASR+MT) often suffer from error propagation in the pipeline.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • EMNLP 2021 • Junkun Chen, Renjie Zheng, Atsuhito Kita, Mingbo Ma, Liang Huang
Simultaneous translation is vastly different from full-sentence translation, in the sense that it starts translation before the source sentence ends, with only a few words delay.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Renjie Zheng, Mingbo Ma, Baigong Zheng, Kaibo Liu, Jiahong Yuan, Kenneth Church, Liang Huang
Simultaneous speech-to-speech translation is widely useful but extremely challenging, since it needs to generate target-language speech concurrently with the source-language speech, with only a few seconds delay.
no code implementations • ACL 2020 • Renjie Zheng, Mingbo Ma, Baigong Zheng, Kaibo Liu, Liang Huang
Simultaneous translation has many important application scenarios and attracts much attention from both academia and industry recently.
no code implementations • ACL 2020 • Baigong Zheng, Kaibo Liu, Renjie Zheng, Mingbo Ma, Hairong Liu, Liang Huang
Adaptive policies are better than fixed policies for simultaneous translation, since they can flexibly balance the tradeoff between translation quality and latency based on the current context information.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Mingbo Ma, Baigong Zheng, Kaibo Liu, Renjie Zheng, Hairong Liu, Kainan Peng, Kenneth Church, Liang Huang
Text-to-speech synthesis (TTS) has witnessed rapid progress in recent years, where neural methods became capable of producing audios with high naturalness.
no code implementations • IJCNLP 2019 • Renjie Zheng, Mingbo Ma, Baigong Zheng, Liang Huang
Beam search is universally used in full-sentence translation but its application to simultaneous translation remains non-trivial, where output words are committed on the fly.
no code implementations • IJCNLP 2019 • Baigong Zheng, Renjie Zheng, Mingbo Ma, Liang Huang
Simultaneous translation is widely useful but remains challenging.
no code implementations • WS 2019 • Renjie Zheng, Hairong Liu, Mingbo Ma, Baigong Zheng, Liang Huang
To make it worse, the amount of social media parallel corpora is extremely limited.
no code implementations • ACL 2019 • Baigong Zheng, Renjie Zheng, Mingbo Ma, Liang Huang
Simultaneous translation is widely useful but remains one of the most difficult tasks in NLP.
no code implementations • NAACL 2019 • Mingbo Ma, Renjie Zheng, Liang Huang
Beam search optimization resolves many issues in neural machine translation.
3 code implementations • ACL 2019 • Mingbo Ma, Liang Huang, Hao Xiong, Renjie Zheng, Kaibo Liu, Baigong Zheng, Chuanqiang Zhang, Zhongjun He, Hairong Liu, Xing Li, Hua Wu, Haifeng Wang
Simultaneous translation, which translates sentences before they are finished, is useful in many scenarios but is notoriously difficult due to word-order differences.
no code implementations • WS 2018 • Renjie Zheng, Yilin Yang, Mingbo Ma, Liang Huang
This paper describes multimodal machine translation systems developed jointly by Oregon State University and Baidu Research for WMT 2018 Shared Task on multimodal translation.
no code implementations • EMNLP 2018 • Renjie Zheng, Mingbo Ma, Liang Huang
Neural text generation, including neural machine translation, image captioning, and summarization, has been quite successful recently.
no code implementations • 22 Apr 2018 • Renjie Zheng, Junkun Chen, Xipeng Qiu
More specifically, all tasks share the same sentence representation and each task can select the task-specific information from the shared sentence representation with attention mechanism.