Search Results for author: Changhan Wang

Found 35 papers, 13 papers with code

Findings of the IWSLT 2022 Evaluation Campaign

no code implementations IWSLT (ACL) 2022 Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, Marcely Zanon Boito, Ondřej Bojar, Roldano Cattoni, Anna Currey, Georgiana Dinu, Kevin Duh, Maha Elbayad, Clara Emmanuel, Yannick Estève, Marcello Federico, Christian Federmann, Souhir Gahbiche, Hongyu Gong, Roman Grundkiewicz, Barry Haddow, Benjamin Hsu, Dávid Javorský, Vĕra Kloudová, Surafel Lakew, Xutai Ma, Prashant Mathur, Paul McNamee, Kenton Murray, Maria Nǎdejde, Satoshi Nakamura, Matteo Negri, Jan Niehues, Xing Niu, John Ortega, Juan Pino, Elizabeth Salesky, Jiatong Shi, Matthias Sperber, Sebastian Stüker, Katsuhito Sudoh, Marco Turchi, Yogesh Virkar, Alexander Waibel, Changhan Wang, Shinji Watanabe

The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation.

Speech-to-Speech Translation Translation

Facebook AI’s WMT20 News Translation Task Submission

no code implementations WMT (EMNLP) 2020 Peng-Jen Chen, Ann Lee, Changhan Wang, Naman Goyal, Angela Fan, Mary Williamson, Jiatao Gu

We approach the low resource problem using two main strategies, leveraging all available data and adapting the system to the target news domain.

Data Augmentation Translation

FINDINGS OF THE IWSLT 2021 EVALUATION CAMPAIGN

no code implementations ACL (IWSLT) 2021 Antonios Anastasopoulos, Ondřej Bojar, Jacob Bremerman, Roldano Cattoni, Maha Elbayad, Marcello Federico, Xutai Ma, Satoshi Nakamura, Matteo Negri, Jan Niehues, Juan Pino, Elizabeth Salesky, Sebastian Stüker, Katsuhito Sudoh, Marco Turchi, Alexander Waibel, Changhan Wang, Matthew Wiesner

The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2021) featured this year four shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Multilingual speech translation, (iv) Low-resource speech translation.

Translation

Enhanced Direct Speech-to-Speech Translation Using Self-supervised Pre-training and Data Augmentation

no code implementations6 Apr 2022 Sravya Popuri, Peng-Jen Chen, Changhan Wang, Juan Pino, Yossi Adi, Jiatao Gu, Wei-Ning Hsu, Ann Lee

Direct speech-to-speech translation (S2ST) models suffer from data scarcity issues as there exists little parallel S2ST data, compared to the amount of data available for conventional cascaded systems that consist of automatic speech recognition (ASR), machine translation (MT), and text-to-speech (TTS) synthesis.

Automatic Speech Recognition Data Augmentation +4

Textless Speech-to-Speech Translation on Real Data

no code implementations15 Dec 2021 Ann Lee, Hongyu Gong, Paul-Ambroise Duquenne, Holger Schwenk, Peng-Jen Chen, Changhan Wang, Sravya Popuri, Yossi Adi, Juan Pino, Jiatao Gu, Wei-Ning Hsu

To our knowledge, we are the first to establish a textless S2ST technique that can be trained with real-world data and works for multiple language pairs.

Speech-to-Speech Translation Translation

XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

1 code implementation17 Nov 2021 Arun Babu, Changhan Wang, Andros Tjandra, Kushal Lakhotia, Qiantong Xu, Naman Goyal, Kritika Singh, Patrick von Platen, Yatharth Saraf, Juan Pino, Alexei Baevski, Alexis Conneau, Michael Auli

On the CoVoST-2 speech translation benchmark, we improve the previous state of the art by an average of 7. 4 BLEU over 21 translation directions into English.

 Ranked #1 on Speech Recognition on Common Voice German (using extra training data)

14 Language Identification +3

Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation

no code implementations ICLR 2022 Xuan-Phi Nguyen, Hongyu Gong, Yun Tang, Changhan Wang, Philipp Koehn, Shafiq Joty

Modern unsupervised machine translation systems mostly train their models by generating synthetic parallel training data from large unlabeled monolingual corpora of different languages through various means, such as iterative back-translation.

14 Translation +1

Multilingual Speech Translation from Efficient Finetuning of Pretrained Models

no code implementations ACL 2021 Xian Li, Changhan Wang, Yun Tang, Chau Tran, Yuqing Tang, Juan Pino, Alexei Baevski, Alexis Conneau, Michael Auli

We present a simple yet effective approach to build multilingual speech-to-text (ST) translation through efficient transfer learning from a pretrained speech encoder and text decoder.

Text Generation Transfer Learning +1

FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task

no code implementations ACL (IWSLT) 2021 Yun Tang, Hongyu Gong, Xian Li, Changhan Wang, Juan Pino, Holger Schwenk, Naman Goyal

In this paper, we describe our end-to-end multilingual speech translation system submitted to the IWSLT 2021 evaluation campaign on the Multilingual Speech Translation shared task.

Transfer Learning Translation

Direct speech-to-speech translation with discrete units

no code implementations ACL 2022 Ann Lee, Peng-Jen Chen, Changhan Wang, Jiatao Gu, Sravya Popuri, Xutai Ma, Adam Polyak, Yossi Adi, Qing He, Yun Tang, Juan Pino, Wei-Ning Hsu

When target text transcripts are available, we design a joint speech and text training framework that enables the model to generate dual modality output (speech and text) simultaneously in the same inference pass.

Speech-to-Speech Translation Text Generation +1

Large-Scale Self- and Semi-Supervised Learning for Speech Translation

no code implementations14 Apr 2021 Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli, Alexis Conneau

In this paper, we improve speech translation (ST) through effectively leveraging large quantities of unlabeled speech and text data in different and complementary ways.

Language Modelling Translation

Facebook AI's WMT20 News Translation Task Submission

no code implementations16 Nov 2020 Peng-Jen Chen, Ann Lee, Changhan Wang, Naman Goyal, Angela Fan, Mary Williamson, Jiatao Gu

We approach the low resource problem using two main strategies, leveraging all available data and adapting the system to the target news domain.

Data Augmentation Translation

Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech Translation

1 code implementation COLING 2020 Hang Le, Juan Pino, Changhan Wang, Jiatao Gu, Didier Schwab, Laurent Besacier

We propose two variants of these architectures corresponding to two different levels of dependencies between the decoders, called the parallel and cross dual-decoder Transformers, respectively.

Automatic Speech Recognition Speech-to-Text Translation +1

Multilingual Speech Translation with Efficient Finetuning of Pretrained Models

no code implementations24 Oct 2020 Xian Li, Changhan Wang, Yun Tang, Chau Tran, Yuqing Tang, Juan Pino, Alexei Baevski, Alexis Conneau, Michael Auli

We present a simple yet effective approach to build multilingual speech-to-text (ST) translation by efficient transfer learning from pretrained speech encoder and text decoder.

Cross-Lingual Transfer Text Generation +2

A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks

no code implementations21 Oct 2020 Yun Tang, Juan Pino, Changhan Wang, Xutai Ma, Dmitriy Genzel

We demonstrate that representing text input as phoneme sequences can reduce the difference between speech and text inputs, and enhance the knowledge transfer from text corpora to the speech to text tasks.

Automatic Speech Recognition Denoising +3

CoVoST 2 and Massively Multilingual Speech-to-Text Translation

1 code implementation20 Jul 2020 Changhan Wang, Anne Wu, Juan Pino

Speech translation has recently become an increasingly popular topic of research, partly due to the development of benchmark datasets.

Machine Translation Speech Recognition +2

FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN

no code implementations WS 2020 Ebrahim Ansari, Amittai Axelrod, Nguyen Bach, Ond{\v{r}}ej Bojar, Roldano Cattoni, Fahim Dalvi, Nadir Durrani, Marcello Federico, Christian Federmann, Jiatao Gu, Fei Huang, Kevin Knight, Xutai Ma, Ajay Nagesh, Matteo Negri, Jan Niehues, Juan Pino, Elizabeth Salesky, Xing Shi, Sebastian St{\"u}ker, Marco Turchi, Alex Waibel, er, Changhan Wang

The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2020) featured this year six challenge tracks: (i) Simultaneous speech translation, (ii) Video speech translation, (iii) Offline speech translation, (iv) Conversational speech translation, (v) Open domain translation, and (vi) Non-native speech translation.

Translation

Self-Supervised Representations Improve End-to-End Speech Translation

no code implementations22 Jun 2020 Anne Wu, Changhan Wang, Juan Pino, Jiatao Gu

End-to-end speech-to-text translation can provide a simpler and smaller system but is facing the challenge of data scarcity.

Cross-Lingual Transfer Speech Recognition +2

Improving Cross-Lingual Transfer Learning for End-to-End Speech Recognition with Speech Translation

no code implementations9 Jun 2020 Changhan Wang, Juan Pino, Jiatao Gu

Even with pseudo-labels from low-resource MT (200K examples), ST-enhanced transfer brings up to 8. 9% WER reduction to direct transfer.

Automatic Speech Recognition Cross-Lingual Transfer +4

CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus

1 code implementation LREC 2020 Changhan Wang, Juan Pino, Anne Wu, Jiatao Gu

Spoken language translation has recently witnessed a resurgence in popularity, thanks to the development of end-to-end models and the creation of new corpora, such as Augmented LibriSpeech and MuST-C.

Speech-to-Text Translation Translation

VizSeq: A Visual Analysis Toolkit for Text Generation Tasks

1 code implementation IJCNLP 2019 Changhan Wang, Anirudh Jain, Danlu Chen, Jiatao Gu

Automatic evaluation of text generation tasks (e. g. machine translation, text summarization, image captioning and video description) usually relies heavily on task-specific metrics, such as BLEU and ROUGE.

Image Captioning Machine Translation +4

Neural Machine Translation with Byte-Level Subwords

1 code implementation7 Sep 2019 Changhan Wang, Kyunghyun Cho, Jiatao Gu

Representing text at the level of bytes and using the 256 byte set as vocabulary is a potential solution to this issue.

Machine Translation Translation

Does Object Recognition Work for Everyone?

no code implementations6 Jun 2019 Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten

The paper analyzes the accuracy of publicly available object-recognition systems on a geographically diverse dataset.

Object Recognition

Levenshtein Transformer

2 code implementations NeurIPS 2019 Jiatao Gu, Changhan Wang, Jake Zhao

We further confirm the flexibility of our model by showing a Levenshtein Transformer trained by machine translation can straightforwardly be used for automatic post-editing.

Automatic Post-Editing Text Summarization +1

Dynamic Meta-Embeddings for Improved Sentence Representations

3 code implementations EMNLP 2018 Douwe Kiela, Changhan Wang, Kyunghyun Cho

While one of the first steps in many NLP systems is selecting what pre-trained word embeddings to use, we argue that such a step is better left for neural networks to figure out by themselves.

Word Embeddings

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