Search Results for author: Naveen Arivazhagan

Found 17 papers, 4 papers with code

Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents

no code implementations ACL 2022 Biao Zhang, Ankur Bapna, Melvin Johnson, Ali Dabirmoghaddam, Naveen Arivazhagan, Orhan Firat

Using simple concatenation-based DocNMT, we explore the effect of 3 factors on the transfer: the number of teacher languages with document level data, the balance between document and sentence level data at training, and the data condition of parallel documents (genuine vs. backtranslated).

Machine Translation Transfer Learning +1

Simultaneous Translation

no code implementations EMNLP 2020 Liang Huang, Colin Cherry, Mingbo Ma, Naveen Arivazhagan, Zhongjun He

Simultaneous translation, which performs translation concurrently with the source speech, is widely useful in many scenarios such as international conferences, negotiations, press releases, legal proceedings, and medicine.

Machine Translation Speech Recognition +2

Sentence Boundary Augmentation For Neural Machine Translation Robustness

no code implementations21 Oct 2020 Daniel Li, Te I, Naveen Arivazhagan, Colin Cherry, Dirk Padfield

Specifically, in the context of long-form speech translation systems, where the input transcripts come from Automatic Speech Recognition (ASR), the NMT models have to handle errors including phoneme substitutions, grammatical structure, and sentence boundaries, all of which pose challenges to NMT robustness.

Automatic Speech Recognition Data Augmentation +2

Language-agnostic BERT Sentence Embedding

5 code implementations ACL 2022 Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, Naveen Arivazhagan, Wei Wang

While BERT is an effective method for learning monolingual sentence embeddings for semantic similarity and embedding based transfer learning (Reimers and Gurevych, 2019), BERT based cross-lingual sentence embeddings have yet to be explored.

Language Modelling Masked Language Modeling +7

Re-translation versus Streaming for Simultaneous Translation

no code implementations WS 2020 Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, George Foster

There has been great progress in improving streaming machine translation, a simultaneous paradigm where the system appends to a growing hypothesis as more source content becomes available.

Data Augmentation Machine Translation +1

Controlling Computation versus Quality for Neural Sequence Models

no code implementations17 Feb 2020 Ankur Bapna, Naveen Arivazhagan, Orhan Firat

Further, methods that adapt the amount of computation to the example focus on finding a fixed inference-time computational graph per example, ignoring any external computational budgets or varying inference time limitations.

Representation Learning

Re-Translation Strategies For Long Form, Simultaneous, Spoken Language Translation

1 code implementation6 Dec 2019 Naveen Arivazhagan, Colin Cherry, Te I, Wolfgang Macherey, Pallavi Baljekar, George Foster

As this scenario allows for revisions to our incremental translations, we adopt a re-translation approach to simultaneous translation, where the source is repeatedly translated from scratch as it grows.

Machine Translation Speech Recognition +1

Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation

no code implementations1 Sep 2019 Aditya Siddhant, Melvin Johnson, Henry Tsai, Naveen Arivazhagan, Jason Riesa, Ankur Bapna, Orhan Firat, Karthik Raman

The recently proposed massively multilingual neural machine translation (NMT) system has been shown to be capable of translating over 100 languages to and from English within a single model.

Cross-Lingual Transfer Machine Translation +2

Small and Practical BERT Models for Sequence Labeling

no code implementations IJCNLP 2019 Henry Tsai, Jason Riesa, Melvin Johnson, Naveen Arivazhagan, Xin Li, Amelia Archer

We propose a practical scheme to train a single multilingual sequence labeling model that yields state of the art results and is small and fast enough to run on a single CPU.

Part-Of-Speech Tagging

Monotonic Infinite Lookback Attention for Simultaneous Machine Translation

no code implementations ACL 2019 Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, Chung-Cheng Chiu, Semih Yavuz, Ruoming Pang, Wei Li, Colin Raffel

Simultaneous machine translation begins to translate each source sentence before the source speaker is finished speaking, with applications to live and streaming scenarios.

Machine Translation Translation

The Missing Ingredient in Zero-Shot Neural Machine Translation

no code implementations17 Mar 2019 Naveen Arivazhagan, Ankur Bapna, Orhan Firat, Roee Aharoni, Melvin Johnson, Wolfgang Macherey

Multilingual Neural Machine Translation (NMT) models are capable of translating between multiple source and target languages.

Machine Translation Translation

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