Ankur Bapna

According to our database1, Ankur Bapna authored at least 56 papers between 2017 and 2023.

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Bibliography

2023
Multimodal Modeling For Spoken Language Identification.
CoRR, 2023

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset.
CoRR, 2023

AudioPaLM: A Large Language Model That Can Speak and Listen.
CoRR, 2023

Label Aware Speech Representation Learning For Language Identification.
CoRR, 2023

LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus.
CoRR, 2023

Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages.
CoRR, 2023

Miipher: A Robust Speech Restoration Model Integrating Self-Supervised Speech and Text Representations.
Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2023

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mu<sup>2</sup>SLAM: Multitask, Multilingual Speech and Language Models.
Proceedings of the International Conference on Machine Learning, 2023

Understanding Shared Speech-Text Representations.
Proceedings of the IEEE International Conference on Acoustics, 2023

SQuId: Measuring Speech Naturalness in Many Languages.
Proceedings of the IEEE International Conference on Acoustics, 2023

Virtuoso: Massive Multilingual Speech-Text Joint Semi-Supervised Learning for Text-to-Speech.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets.
Trans. Assoc. Comput. Linguistics, 2022

Building Machine Translation Systems for the Next Thousand Languages.
CoRR, 2022

mSLAM: Massively multilingual joint pre-training for speech and text.
CoRR, 2022

Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning.
CoRR, 2022

JOIST: A Joint Speech and Text Streaming Model for ASR.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Maestro-U: Leveraging Joint Speech-Text Representation Learning for Zero Supervised Speech ASR.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Leveraging unsupervised and weakly-supervised data to improve direct speech-to-speech translation.
Proceedings of the Interspeech 2022, 2022


MAESTRO: Matched Speech Text Representations through Modality Matching.
Proceedings of the Interspeech 2022, 2022

Examining Scaling and Transfer of Language Model Architectures for Machine Translation.
Proceedings of the International Conference on Machine Learning, 2022

Scaling Laws for Neural Machine Translation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Joint Unsupervised and Supervised Training for Multilingual ASR.
Proceedings of the IEEE International Conference on Acoustics, 2022

Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training.
CoRR, 2021

Gradient-guided Loss Masking for Neural Machine Translation.
CoRR, 2021

Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation.
Proceedings of the 9th International Conference on Learning Representations, 2021

Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020
Controlling Computation versus Quality for Neural Sequence Models.
CoRR, 2020

Faster Transformer Decoding: N-gram Masked Self-Attention.
CoRR, 2020

Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Fill in the Blanks: Imputing Missing Sentences for Larger-Context Neural Machine Translation.
CoRR, 2019

Simple, Scalable Adaptation for Neural Machine Translation.
CoRR, 2019

Investigating Multilingual NMT Representations at Scale.
CoRR, 2019

Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation.
CoRR, 2019

Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges.
CoRR, 2019

The Missing Ingredient in Zero-Shot Neural Machine Translation.
CoRR, 2019

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling.
CoRR, 2019

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Non-Parametric Adaptation for Neural Machine Translation.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model.
Proceedings of the Interspeech 2019, 2019

Investigating Multilingual NMT Representations at Scale.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Simple, Scalable Adaptation for Neural Machine Translation.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018
The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation.
CoRR, 2018

Building a Conversational Agent Overnight with Dialogue Self-Play.
CoRR, 2018

Revisiting Character-Based Neural Machine Translation with Capacity and Compression.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Training Deeper Neural Machine Translation Models with Transparent Attention.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
Improving Frame Semantic Parsing with Hierarchical Dialogue Encoders.
CoRR, 2017

Sequential Dialogue Context Modeling for Spoken Language Understanding.
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, 2017

Towards Zero-Shot Frame Semantic Parsing for Domain Scaling.
Proceedings of the Interspeech 2017, 2017


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