Search Results for author: Thanh-Le Ha

Found 36 papers, 4 papers with code

Improving Multilingual Neural Machine Translation For Low-Resource Languages: French, English - Vietnamese

no code implementations loresmt (AACL) 2020 Thi-Vinh Ngo, Phuong-Thai Nguyen, Thanh-Le Ha, Khac-Quy Dinh, Le-Minh Nguyen

Prior works have demonstrated that a low-resource language pair can benefit from multilingual machine translation (MT) systems, which rely on many language pairs’ joint training.

Machine Translation Translation +1

The IWSLT 2019 Evaluation Campaign

no code implementations EMNLP (IWSLT) 2019 Jan Niehues, Rolando Cattoni, Sebastian Stüker, Matteo Negri, Marco Turchi, Thanh-Le Ha, Elizabeth Salesky, Ramon Sanabria, Loic Barrault, Lucia Specia, Marcello Federico

The IWSLT 2019 evaluation campaign featured three tasks: speech translation of (i) TED talks and (ii) How2 instructional videos from English into German and Portuguese, and (iii) text translation of TED talks from English into Czech.

Translation

Multilingual Speech Translation KIT @ IWSLT2021

no code implementations ACL (IWSLT) 2021 Ngoc-Quan Pham, Tuan Nam Nguyen, Thanh-Le Ha, Sebastian Stüker, Alexander Waibel, Dan He

This paper contains the description for the submission of Karlsruhe Institute of Technology (KIT) for the multilingual TEDx translation task in the IWSLT 2021 evaluation campaign.

Translation

KIT’s Multilingual Neural Machine Translation systems for IWSLT 2017

no code implementations IWSLT 2017 Ngoc-Quan Pham, Matthias Sperber, Elizabeth Salesky, Thanh-Le Ha, Jan Niehues, Alexander Waibel

For the SLT track, in addition to a monolingual neural translation system used to generate correct punctuations and true cases of the data prior to training our multilingual system, we introduced a noise model in order to make our system more robust.

Machine Translation NMT +1

Improving Multilingual Neural Machine Translation For Low-Resource Languages: French,English - Vietnamese

no code implementations16 Dec 2020 Thi-Vinh Ngo, Phuong-Thai Nguyen, Thanh-Le Ha, Khac-Quy Dinh, Le-Minh Nguyen

Prior works have demonstrated that a low-resource language pair can benefit from multilingual machine translation (MT) systems, which rely on many language pairs' joint training.

Machine Translation Translation +1

Relative Positional Encoding for Speech Recognition and Direct Translation

no code implementations20 May 2020 Ngoc-Quan Pham, Thanh-Le Ha, Tuan-Nam Nguyen, Thai-Son Nguyen, Elizabeth Salesky, Sebastian Stueker, Jan Niehues, Alexander Waibel

We also show that this model is able to better utilize synthetic data than the Transformer, and adapts better to variable sentence segmentation quality for speech translation.

Position Sentence +4

Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation

no code implementations WS 2019 Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen, Le-Minh Nguyen

Among the six challenges of neural machine translation (NMT) coined by (Koehn and Knowles, 2017), rare-word problem is considered the most severe one, especially in translation of low-resource languages.

Machine Translation NMT +1

Low-Latency Neural Speech Translation

no code implementations1 Aug 2018 Jan Niehues, Ngoc-Quan Pham, Thanh-Le Ha, Matthias Sperber, Alex Waibel

After adaptation, we are able to reduce the number of corrections displayed during incremental output construction by 45%, without a decrease in translation quality.

Machine Translation Multi-Task Learning +3

Combining Advanced Methods in Japanese-Vietnamese Neural Machine Translation

1 code implementation18 May 2018 Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen, Le-Minh Nguyen

Neural machine translation (NMT) systems have recently obtained state-of-the art in many machine translation systems between popular language pairs because of the availability of data.

Machine Translation NMT +1

Effective Strategies in Zero-Shot Neural Machine Translation

1 code implementation IWSLT 2017 Thanh-Le Ha, Jan Niehues, Alexander Waibel

In this paper, we proposed two strategies which can be applied to a multilingual neural machine translation system in order to better tackle zero-shot scenarios despite not having any parallel corpus.

Machine Translation Translation

Analyzing Neural MT Search and Model Performance

no code implementations WS 2017 Jan Niehues, Eunah Cho, Thanh-Le Ha, Alex Waibel

By separating the search space and the modeling using $n$-best list reranking, we analyze the influence of both parts of an NMT system independently.

NMT Translation

Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder

no code implementations IWSLT 2016 Thanh-Le Ha, Jan Niehues, Alexander Waibel

In this paper, we present our first attempts in building a multilingual Neural Machine Translation framework under a unified approach.

Machine Translation NMT +1

Lexical Translation Model Using a Deep Neural Network Architecture

no code implementations28 Apr 2015 Thanh-Le Ha, Jan Niehues, Alex Waibel

In this paper we combine the advantages of a model using global source sentence contexts, the Discriminative Word Lexicon, and neural networks.

Sentence Translation

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