b'Raj Dabre'

research

∙ 07/31/2023

SelfSeg: A Self-supervised Sub-word Segmentation Method for Neural Machine Translation

Sub-word segmentation is an essential pre-processing step for Neural Mac...

0 Haiyue Song, et al. ∙

research

∙ 07/27/2023

Turning Whisper into Real-Time Transcription System

Whisper is one of the recent state-of-the-art multilingual speech recogn...

0 Dominik Macháček, et al. ∙

research

∙ 06/06/2023

SciCap+: A Knowledge Augmented Dataset to Study the Challenges of Scientific Figure Captioning

In scholarly documents, figures provide a straightforward way of communi...

0 Zhishen Yang, et al. ∙

research

∙ 05/26/2023

Robustness of Multi-Source MT to Transcription Errors

Automatic speech translation is sensitive to speech recognition errors, ...

0 Dominik Macháček, et al. ∙

research

∙ 05/25/2023

IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages

India has a rich linguistic landscape with languages from 4 major langua...

0 AI4Bharat, et al. ∙

research

∙ 05/23/2023

In-context Example Selection for Machine Translation Using Multiple Features

Large language models have demonstrated the capability to perform well o...

0 Aswanth Kumar, et al. ∙

research

∙ 05/22/2023

Decomposed Prompting for Machine Translation Between Related Languages using Large Language Models

This study investigates machine translation between related languages i....

0 Ratish Puduppully, et al. ∙

research

∙ 05/17/2023

Variable-length Neural Interlingua Representations for Zero-shot Neural Machine Translation

The language-independency of encoded representations within multilingual...

0 Zhuoyuan Mao, et al. ∙

research

∙ 05/16/2023

Exploring the Impact of Layer Normalization for Zero-shot Neural Machine Translation

This paper studies the impact of layer normalization (LayerNorm) on zero...

0 Zhuoyuan Mao, et al. ∙

research

∙ 05/12/2023

A Comprehensive Analysis of Adapter Efficiency

Adapters have been positioned as a parameter-efficient fine-tuning (PEFT...

0 Nandini Mundra, et al. ∙

research

∙ 04/19/2023

An Empirical Study of Leveraging Knowledge Distillation for Compressing Multilingual Neural Machine Translation Models

Knowledge distillation (KD) is a well-known method for compressing neura...

4 Varun Gumma, et al. ∙

research

∙ 12/20/2022

IndicMT Eval: A Dataset to Meta-Evaluate Machine Translation metrics for Indian Languages

The rapid growth of machine translation (MT) systems has necessitated co...

0 Ananya B. Sai, et al. ∙

research

∙ 11/16/2022

MT Metrics Correlate with Human Ratings of Simultaneous Speech Translation

There have been several studies on the correlation between human ratings...

0 Dominik Macháček, et al. ∙

research

∙ 06/06/2022

MorisienMT: A Dataset for Mauritian Creole Machine Translation

In this paper, we describe MorisienMT, a dataset for benchmarking machin...

0 Raj Dabre, et al. ∙

research

∙ 04/26/2022

When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?

Word alignment has proven to benefit many-to-many neural machine transla...

1 Zhuoyuan Mao, et al. ∙

research

∙ 04/11/2022

Fusion of Self-supervised Learned Models for MOS Prediction

We participated in the mean opinion score (MOS) prediction challenge, 20...

0 Zhengdong Yang, et al. ∙

research

∙ 12/16/2021

Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages

Cognates are variants of the same lexical form across different language...

1 Diptesh Kanojia, et al. ∙

research

∙ 09/07/2021

IndicBART: A Pre-trained Model for Natural Language Generation of Indic Languages

In this paper we present IndicBART, a multilingual, sequence-to-sequence...

7 Raj Dabre, et al. ∙

research

∙ 08/25/2021

YANMTT: Yet Another Neural Machine Translation Toolkit

In this paper we present our open-source neural machine translation (NMT...

0 Raj Dabre, et al. ∙

research

∙ 06/18/2021

Recurrent Stacking of Layers in Neural Networks: An Application to Neural Machine Translation

In deep neural network modeling, the most common practice is to stack a ...

0 Raj Dabre, et al. ∙

research

∙ 04/15/2021

Simultaneous Multi-Pivot Neural Machine Translation

Parallel corpora are indispensable for training neural machine translati...

0 Raj Dabre, et al. ∙

research

∙ 09/20/2020

Softmax Tempering for Training Neural Machine Translation Models

Neural machine translation (NMT) models are typically trained using a so...

0 Raj Dabre, et al. ∙

research

∙ 05/07/2020

JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation

Neural machine translation (NMT) needs large parallel corpora for state-...

0 Zhuoyuan Mao, et al. ∙

research

∙ 02/20/2020

Balancing Cost and Benefit with Tied-Multi Transformers

We propose and evaluate a novel procedure for training multiple Transfor...

0 Raj Dabre, et al. ∙

research

∙ 01/23/2020

Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation

Sequence-to-sequence (S2S) pre-training using large monolingual data is ...

0 Haiyue Song, et al. ∙

research

∙ 01/04/2020

A Comprehensive Survey of Multilingual Neural Machine Translation

We present a survey on multilingual neural machine translation (MNMT), w...

0 Raj Dabre, et al. ∙

research

∙ 12/26/2019

Coursera Corpus Mining and Multistage Fine-Tuning for Improving Lectures Translation

Lectures translation is a case of spoken language translation and there ...

0 Haiyue Song, et al. ∙

research

∙ 08/27/2019

Multi-Layer Softmaxing during Training Neural Machine Translation for Flexible Decoding with Fewer Layers

This paper proposes a novel procedure for training an encoder-decoder ba...

0 Raj Dabre, et al. ∙

research

∙ 07/06/2019

Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation

This paper proposes a novel multilingual multistage fine-tuning approach...

0 Aizhan Imankulova, et al. ∙

research

∙ 06/19/2019

Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation

In this paper, we propose two novel methods for domain adaptation for th...

0 Chenhui Chu, et al. ∙

research

∙ 05/14/2019

A Survey of Multilingual Neural Machine Translation

We present a survey on multilingual neural machine translation (MNMT), w...

0 Raj Dabre, et al. ∙

research

∙ 07/14/2018

Recurrent Stacking of Layers for Compact Neural Machine Translation Models

In Neural Machine Translation (NMT), the most common practice is to stac...

0 Raj Dabre, et al. ∙

research

∙ 10/03/2017

MMCR4NLP: Multilingual Multiway Corpora Repository for Natural Language Processing

Multilinguality is gradually becoming ubiquitous in the sense that more ...

0 Raj Dabre, et al. ∙

research

∙ 02/20/2017

Enabling Multi-Source Neural Machine Translation By Concatenating Source Sentences In Multiple Languages

In this paper, we propose a novel and elegant solution to "Multi-Source ...

0 Raj Dabre, et al. ∙

research

∙ 01/12/2017

An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation

In this paper, we propose a novel domain adaptation method named "mixed ...

0 Chenhui Chu, et al. ∙

Raj Dabre

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