Search Results for author: Peng-Jen Chen

Found 22 papers, 10 papers with code

Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment

no code implementations WMT (EMNLP) 2020 Philipp Koehn, Vishrav Chaudhary, Ahmed El-Kishky, Naman Goyal, Peng-Jen Chen, Francisco Guzmán

Following two preceding WMT Shared Task on Parallel Corpus Filtering (Koehn et al., 2018, 2019), we posed again the challenge of assigning sentence-level quality scores for very noisy corpora of sentence pairs crawled from the web, with the goal of sub-selecting the highest-quality data to be used to train ma-chine translation systems.

Sentence 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

UnitY: Two-pass Direct Speech-to-speech Translation with Discrete Units

1 code implementation15 Dec 2022 Hirofumi Inaguma, Sravya Popuri, Ilia Kulikov, Peng-Jen Chen, Changhan Wang, Yu-An Chung, Yun Tang, Ann Lee, Shinji Watanabe, Juan Pino

We enhance the model performance by subword prediction in the first-pass decoder, advanced two-pass decoder architecture design and search strategy, and better training regularization.

Denoising Speech-to-Speech Translation +3

Simple and Effective Unsupervised Speech Translation

no code implementations18 Oct 2022 Changhan Wang, Hirofumi Inaguma, Peng-Jen Chen, Ilia Kulikov, Yun Tang, Wei-Ning Hsu, Michael Auli, Juan Pino

The amount of labeled data to train models for speech tasks is limited for most languages, however, the data scarcity is exacerbated for speech translation which requires labeled data covering two different languages.

Machine Translation speech-recognition +6

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 Automatic Speech Recognition (ASR) +6

Direct Simultaneous Speech-to-Speech Translation with Variational Monotonic Multihead Attention

no code implementations15 Oct 2021 Xutai Ma, Hongyu Gong, Danni Liu, Ann Lee, Yun Tang, Peng-Jen Chen, Wei-Ning Hsu, Phillip Koehn, Juan Pino

We present a direct simultaneous speech-to-speech translation (Simul-S2ST) model, Furthermore, the generation of translation is independent from intermediate text representations.

Speech Synthesis Speech-to-Speech Translation +1

Direct speech-to-speech translation with discrete units

1 code implementation 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

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

Multilingual Translation with Extensible Multilingual Pretraining and Finetuning

5 code implementations2 Aug 2020 Yuqing Tang, Chau Tran, Xi-An Li, Peng-Jen Chen, Naman Goyal, Vishrav Chaudhary, Jiatao Gu, Angela Fan

Recent work demonstrates the potential of multilingual pretraining of creating one model that can be used for various tasks in different languages.

Machine Translation Translation

The Source-Target Domain Mismatch Problem in Machine Translation

no code implementations EACL 2021 Jiajun Shen, Peng-Jen Chen, Matt Le, Junxian He, Jiatao Gu, Myle Ott, Michael Auli, Marc'Aurelio Ranzato

While we live in an increasingly interconnected world, different places still exhibit strikingly different cultures and many events we experience in our every day life pertain only to the specific place we live in.

Machine Translation Translation

Cannot find the paper you are looking for? You can Submit a new open access paper.