Reading List for Multilingual NLP

bib file for this list.

Bilingual Translation

  1. Jiang, Qingnan, Mingxuan Wang, Jun Cao, Shanbo Cheng, Shujian Huang, and Lei Li. 2021. “Learning Kernel-Smoothed Machine Translation with Retrieved Examples.” In Proc. Of EMNLP, 7280–90. https://aclanthology.org/2021.emnlp-main.579.
  2. Khandelwal, Urvashi, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2021. “Nearest Neighbor Machine Translation.” In Proc. Of ICLR. https://openreview.net/forum?id=7wCBOfJ8hJM.
  3. Liang, Jianze, Chengqi Zhao, Mingxuan Wang, Xipeng Qiu, and Lei Li. 2021. “Finding Sparse Structure for Domain Specific Neural Machine Translation.” In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
  4. Sun, Zewei, Mingxuan Wang, Hao Zhou, Chengqi Zhao, Shujian Huang, Jiajun Chen, and Lei Li. 2022. “Rethinking Document-Level Neural Machine Translation.” In Findings of the Association for Computational Linguistics: ACL 2022, 3537–48. https://aclanthology.org/2022.findings-acl.279.
  5. Xu, Jingjing, Hao Zhou, Chun Gan, Zaixiang Zheng, and Lei Li. 2021. “Vocabulary Learning via Optimal Transport for Neural Machine Translation.” In Proc. Of ACL, 7361–73. https://aclanthology.org/2021.acl-long.571.

Multilingual Translation

  1. Yuan, Fei, Yinquan Lu, Wenhao Zhu, Lingpeng Kong, Lei Li, and Jingjing Xu. 2023. “Lego-MT: Learning Detachable Models for Massively Multilingual Machine Translation” In The 61st Annual Meeting of the Association for Computational Linguistics - Findings (ACL-Findings).
  2. Costa-jussà, Marta Ruiz, James Cross, Onur cCelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, et al. 2022. “No Language Left Behind: Scaling Human-Centered Machine Translation.” ArXiv Preprint abs/2207.04672. https://arxiv.org/abs/2207.04672.
  3. Pan, Xiao, Mingxuan Wang, Liwei Wu, and Lei Li. 2021. “Contrastive Learning for Many-to-Many Multilingual Neural Machine Translation.” In Proc. Of ACL, 244–58. https://aclanthology.org/2021.acl-long.21.
  4. Fan, Angela, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, et al. 2021. “Beyond English-Centric Multilingual Machine Translation.” J. Mach. Learn. Res. 22: 107:1–48. http://jmlr.org/papers/v22/20-1307.html.
  5. Garcia, Xavier, Yamini Bansal, Colin Cherry, George Foster, Maxim Krikun, Fangxiaoyu Feng, Melvin Johnson, and Orhan Firat. 2023. “The Unreasonable Effectiveness of Few-Shot Learning for Machine Translation.” ArXiv Preprint abs/2302.01398. https://arxiv.org/abs/2302.01398.
  6. Guerreiro, Nuno M, Duarte Alves, Jonas Waldendorf, Barry Haddow, Alexandra Birch, Pierre Colombo, and André FT Martins. 2023. “Hallucinations in Large Multilingual Translation Models.” ArXiv Preprint abs/2303.16104. https://arxiv.org/abs/2303.16104.
  7. Lin, Zehui, Xiao Pan, Mingxuan Wang, Xipeng Qiu, Jiangtao Feng, Hao Zhou, and Lei Li. 2020. “Pre-Training Multilingual Neural Machine Translation by Leveraging Alignment Information.” In Proc. Of EMNLP, 2649–63. https://aclanthology.org/2020.emnlp-main.210.
  8. Lin, Zehui, Liwei Wu, Mingxuan Wang, and Lei Li. 2021. “Learning Language Specific Sub-Network for Multilingual Machine Translation.” In Proc. Of ACL, 293–305. https://aclanthology.org/2021.acl-long.25.
  9. Zhang, Biao, Ankur Bapna, Rico Sennrich, and Orhan Firat. 2021. “Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation.” In Proc. Of ICLR. https://openreview.net/forum?id=Wj4ODo0uyCF.

Large Language Models for MT

  1. Zhu, Wenhao, Hongyi Liu, Qingxiu Dong, Jingjing Xu, shujian Huang, Lingpeng Kong, Jiajun Chen, and Lei Li. 2023. “Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis.” ArXiv Preprint abs/2304.04675. https://arxiv.org/abs/2304.04675.
  2. Agrawal, Sweta, Chunting Zhou, Mike Lewis, Luke Zettlemoyer, and Marjan Ghazvininejad. 2023. “In-Context Examples Selection for Machine Translation.” In Findings of the Association for Computational Linguistics: ACL 2023, 8857–73. https://aclanthology.org/2023.findings-acl.564.
  3. Vilar, David, Markus Freitag, Colin Cherry, Jiaming Luo, Viresh Ratnakar, and George Foster. 2023. “Prompting PaLM for Translation: Assessing Strategies and Performance.” In Proc. Of ACL, 15406–27. https://aclanthology.org/2023.acl-long.859.
  4. Sun, Zewei, Mingxuan Wang, and Lei Li. 2021. “Multilingual Translation via Grafting Pre-Trained Language Models.” In Findings of the Association for Computational Linguistics: EMNLP 2021, 2735–47. https://aclanthology.org/2021.findings-emnlp.233.
  5. Yang, Jiacheng, Mingxuan Wang, Hao Zhou, Chengqi Zhao, Weinan Zhang, Yong Yu, and Lei Li. 2020. “Towards Making the Most of BERT in Neural Machine Translation.” In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, the Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, the Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020, 9378–85. https://aaai.org/ojs/index.php/AAAI/article/view/6479.

Non-Autoregressive Translation

  1. Huang, Fei, Hao Zhou, Yang Liu, Hang Li, and Minlie Huang. 2022. “Directed Acyclic Transformer for Non-Autoregressive Machine Translation.” In International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, edited by Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvári, Gang Niu, and Sivan Sabato, 162:9410–28. Proceedings of Machine Learning Research. https://proceedings.mlr.press/v162/huang22m.html.
  2. Yu Bao, Hao Zhou, Shujian Huang, Dongqi Wang, Lihua Qian, Xinyu Dai, Jiajun Chen, and Lei Li. "latent-GLAT: Glancing at Latent Variables for Parallel Text Generation." ACL 2022. https://aclanthology.org/2022.acl-long.575/
  3. Qian, Lihua, Hao Zhou, Yu Bao, Mingxuan Wang, Lin Qiu, Weinan Zhang, Yong Yu, and Lei Li. 2021. “Glancing Transformer for Non-Autoregressive Neural Machine Translation.” In Proc. Of ACL, 1993–2003. https://aclanthology.org/2021.acl-long.155.
  4. Huang, Chenyang, Hao Zhou, Osmar R. Zaı̈ane, Lili Mou, and Lei Li. 2022. “Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision.” In Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence, IAAI 2022, the Twelveth Symposium on Educational Advances in Artificial Intelligence, EAAI 2022 Virtual Event, February 22 - March 1, 2022, 10776–84. https://ojs.aaai.org/index.php/AAAI/article/view/21323.
  5. Song, Zhenqiao, Hao Zhou, Lihua Qian, Jingjing Xu, Shanbo Cheng, Mingxuan Wang, and Lei Li. 2022. “Switch-GLAT: Multilingual Parallel Machine Translation via Code-Switch Decoder.” In Proc. Of ICLR. https://openreview.net/forum?id=5HvpvYd68b.
  6. Zhu, Yaoming, Jiangtao Feng, Chengqi Zhao, Mingxuan Wang, and Lei Li. 2021. “Counter-Interference Adapter for Multilingual Machine Translation.” In Findings of the Association for Computational Linguistics: EMNLP 2021, 2812–23. https://aclanthology.org/2021.findings-emnlp.240.
  7. Zheng, Zaixiang, Hao Zhou, Shujian Huang, Jiajun Chen, Jingjing Xu, and Lei Li. 2021. “Duplex Sequence-to-Sequence Learning for Reversible Machine Translation.” In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, Virtual, edited by Marc’Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan, 21070–84. https://proceedings.neurips.cc/paper/2021/hash/afecc60f82be41c1b52f6705ec69e0f1-Abstract.html.

Multilingual Representation Learning

  1. Conneau, Alexis, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020. “Unsupervised Cross-Lingual Representation Learning at Scale.” In Proc. Of ACL, 8440–51. https://aclanthology.org/2020.acl-main.747.
  2. Lewis, Mike, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020. “BART: Denoising Sequence-to-Sequence Pre-Training for Natural Language Generation, Translation, and Comprehension.” In Proc. Of ACL, 7871–80. https://aclanthology.org/2020.acl-main.703.
  3. Liu, Yinhan, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020. “Multilingual Denoising Pre-Training for Neural Machine Translation.” Transactions of the Association for Computational Linguistics 8: 726–42. https://aclanthology.org/2020.tacl-1.47.
  4. Ouyang, Xuan, Shuohuan Wang, Chao Pang, Yu Sun, Hao Tian, Hua Wu, and Haifeng Wang. 2021. “ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-Lingual Semantics with Monolingual Corpora.” In Proc. Of EMNLP, 27–38. https://aclanthology.org/2021.emnlp-main.3.
  5. Xue, Linting, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, and Colin Raffel. 2021. “MT5: A Massively Multilingual Pre-Trained Text-to-Text Transformer.” In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 483–98. https://aclanthology.org/2021.naacl-main.41.

Cross-lingual Transfer

  1. Artetxe, Mikel, Vedanuj Goswami, Shruti Bhosale, Angela Fan, and Luke Zettlemoyer. 2023. “Revisiting Machine Translation for Cross-Lingual Classification.” ArXiv Preprint abs/2305.14240. https://arxiv.org/abs/2305.14240.
  2. Machel Reid, Mikel Artetxe. 2023. “On the Role of Parallel Data in Cross-Lingual Transfer Learning.” In Findings of the Association for Computational Linguistics: ACL 2023, 5999–6006. https://aclanthology.org/2023.findings-acl.372.
  3. Wang, Danqing, Jiaze Chen, Hao Zhou, Xipeng Qiu, and Lei Li. 2021. “Contrastive Aligned Joint Learning for Multilingual Summarization.” In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2739–50. https://aclanthology.org/2021.findings-acl.242.
  4. Wu, Qianhui, Zijia Lin, Börje F. Karlsson, Biqing Huang, and Jianguang Lou. 2020. “UniTrans : Unifying Model Transfer and Data Transfer for Cross-Lingual Named Entity Recognition with Unlabeled Data.” In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020, edited by Christian Bessiere, 3926–32. https://doi.org/10.24963/ijcai.2020/543.
  5. Xia, Mengzhou, Guoqing Zheng, Subhabrata Mukherjee, Milad Shokouhi, Graham Neubig, and Ahmed Hassan Awadallah. 2021. “MetaXL: Meta Representation Transformation for Low-Resource Cross-Lingual Learning.” In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 499–511. https://aclanthology.org/2021.naacl-main.42.
  6. Yang, Huiyun, Huadong Chen, Hao Zhou, and Lei Li. 2022. “Enhancing Cross-Lingual Transfer by Manifold Mixup.” In Proc. Of ICLR. https://openreview.net/forum?id=OjPmfr9GkVv.

Speech Translation

  1. Dong, Qianqian, Yaoming Zhu, Mingxuan Wang, and Lei Li. 2022. “Learning When to Translate for Streaming Speech.” In Proc. Of ACL, 680–94. https://aclanthology.org/2022.acl-long.50.
  2. Rong Ye, Mingxuan Wang, Lei Li. 2022. “Cross-Modal Contrastive Learning for Speech Translation.” In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 5099–5113. https://aclanthology.org/2022.naacl-main.376.
  3. Dong, Qianqian, Mingxuan Wang, Hao Zhou, Shuang Xu, Bo Xu, and Lei Li. 2021. “Consecutive Decoding for Speech-to-Text Translation.” In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, the Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 12738–48. https://ojs.aaai.org/index.php/AAAI/article/view/17508.
  4. Han, Chi, Mingxuan Wang, Heng Ji, and Lei Li. 2021. “Learning Shared Semantic Space for Speech-to-Text Translation.” In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2214–25. https://aclanthology.org/2021.findings-acl.195.
  5. Ouyang, Siqi, Rong Ye, and Lei Li. 2023. “WACO: Word-Aligned Contrastive Learning for Speech Translation.” In Proc. Of ACL, 3891–3907. https://aclanthology.org/2023.acl-long.216.
  6. Ye, Rong, Mingxuan Wang, and Lei Li. 2021. “End-to-End Speech Translation via Cross-Modal Progressive Training.” In Proc. Of INTERSPEECH, edited by Hynek Hermansky, Honza Cernocký, Lukás Burget, Lori Lamel, Odette Scharenborg, and Petr Motlı́cek, 2267–71. https://doi.org/10.21437/Interspeech.2021-1065.
  7. Zheng, Renjie, Junkun Chen, Mingbo Ma, and Liang Huang. 2021. “Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation.” In Proc. Of ICML, edited by Marina Meila and Tong Zhang, 139:12736–46. Proceedings of Machine Learning Research. http://proceedings.mlr.press/v139/zheng21a.html.
  8. Ma, Xutai, Yongqiang Wang, Mohammad Javad Dousti, Philipp Koehn, and Juan Pino. 2021. “Streaming Simultaneous Speech Translation with Augmented Memory Transformer,” 7523–27.

Speech Representation Learning

  1. Babu, Arun, Changhan Wang, Andros Tjandra, Kushal Lakhotia, Qiantong Xu, Naman Goyal, Kritika Singh, et al. 2021. “XLS-r: Self-Supervised Cross-Lingual Speech Representation Learning at Scale.” ArXiv Preprint. https://arxiv.org/abs/2111.09296.
  2. Baevski, Alexei, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. “Wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations.” In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, Virtual, edited by Hugo Larochelle, Marc’Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin. https://proceedings.neurips.cc/paper/2020/hash/92d1e1eb1cd6f9fba3227870bb6d7f07-Abstract.html.
  3. Hsu, Wei-Ning, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed. 2021. “HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units.” IEEE/ACM Transactions on Audio, Speech, and Language Processing 29: 3451–60.
  4. Tang, Yun, Hongyu Gong, Ning Dong, Changhan Wang, Wei-Ning Hsu, Jiatao Gu, Alexei Baevski, et al. 2022. “Unified Speech-Text Pre-Training for Speech Translation and Recognition.” In Proc. Of ACL, 1488–99. https://aclanthology.org/2022.acl-long.105.
  5. Wang, Chengyi, Yu Wu, Yao Qian, Ken’ichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, and Xuedong Huang. 2021. “UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data.” In Proc. Of ICML, edited by Marina Meila and Tong Zhang, 139:10937–47. Proceedings of Machine Learning Research. http://proceedings.mlr.press/v139/wang21y.html.
  6. Zhang, Ziqiang, Long Zhou, Junyi Ao, Shujie Liu, Lirong Dai, Jinyu Li, and Furu Wei. 2022. “SpeechUT: Bridging Speech and Text with Hidden-Unit for Encoder-Decoder Based Speech-Text Pre-Training.” In Proc. Of EMNLP, 1663–76. https://aclanthology.org/2022.emnlp-main.108.

Automatic Speech Recognition

  1. Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine Mcleavey, Ilya Sutskever. Robust Speech Recognition via Large-Scale Weak Supervision. Proceedings of the 40th International Conference on Machine Learning, PMLR 202:28492-28518, 2023. https://proceedings.mlr.press/v202/radford23a.html
  2. Viet Anh Trinh, Pegah Ghahremani, Brian King, Jasha Droppo, Andreas Stolcke, Roland Maas. Reducing Geographic Disparities in Automatic Speech Recognition via Elastic Weight Consolidation. Interspeech 2022.
  3. Vineel Pratap, Andros Tjandra, Bowen Shi, Paden Tomasello, Arun Babu, Sayani Kundu, Ali Elkahky, Zhaoheng Ni, Apoorv Vyas, Maryam Fazel-Zarandi, Alexei Baevski, Yossi Adi, Xiaohui Zhang, Wei-Ning Hsu, Alexis Conneau, Michael Auli. Scaling Speech Technology to 1,000+ Languages. 2023. https://arxiv.org/abs/2305.13516
  4. Zhang et al. Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages, 2023.
  5. Kazuya Kawakami, Luyu Wang, Chris Dyer, Phil Blunsom, Aaron van den Oord. Learning Robust and Multilingual Speech Representations. EMNLP 2020.

Speech Synthesis

  1. Aidan Pine, Dan Wells, Nathan Brinklow, Patrick Littell, Korin Richmond. Requirements and Motivations of Low-Resource Speech Synthesis for Language Revitalization. ACL 2022.
  2. Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, Yuanhao Yi, Lei He, Frank Soong, Tao Qin, Sheng Zhao, Tie-Yan Liu. NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality, 2022. https://arxiv.org/abs/2205.04421

Corpus

  1. Chen, Yiran, Zhenqiao Song, Xianze Wu, Danqing Wang, Jingjing Xu, Jiaze Chen, Hao Zhou, and Lei Li. 2022. “MTG: A Benchmark Suite for Multilingual Text Generation.” In Findings of the Association for Computational Linguistics: NAACL 2022, 2508–27. https://aclanthology.org/2022.findings-naacl.192.
  2. Goyal, Naman, Cynthia Gao, Vishrav Chaudhary, Peng-Jen Chen, Guillaume Wenzek, Da Ju, Sanjana Krishnan, Marc’Aurelio Ranzato, Francisco Guzmán, and Angela Fan. 2022. “The Flores-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation.” Transactions of the Association for Computational Linguistics 10: 522–38. https://aclanthology.org/2022.tacl-1.30.
  3. Ruder, Sebastian, Noah Constant, Jan Botha, Aditya Siddhant, Orhan Firat, Jinlan Fu, Pengfei Liu, et al. 2021. “XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation.” In Proc. Of EMNLP, 10215–45. https://aclanthology.org/2021.emnlp-main.802.
  4. Wang, Changhan, Anne Wu, Jiatao Gu, and Juan Pino. 2021. “CoVoST 2 and Massively Multilingual Speech Translation.” In Proc. Of INTERSPEECH, edited by Hynek Hermansky, Honza Cernocký, Lukás Burget, Lori Lamel, Odette Scharenborg, and Petr Motlı́cek, 2247–51. https://doi.org/10.21437/Interspeech.2021-2027.

Evaluation

  1. Xu, Wenda, Danqing Wang, Liangming Pan, Zhenqiao Song, Markus Freitag, William Yang Wang, and Lei Li. 2023. “Instructscore: Towards Explainable Text Generation Evaluation with Automatic Feedback.” ArXiv Preprint abs/2305.14282. https://arxiv.org/abs/2305.14282.
  2. Xu, Wenda, Xian Qian, Mingxuan Wang, Lei Li, and William Yang Wang. 2023. “SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakes.” In The 61st Annual Meeting of the Association for Computational Linguistics (ACL).
  3. Xu, Wenda, Yi-Lin Tuan, Yujie Lu, Michael Saxon, Lei Li, and William Yang Wang. 2022. “Not All Errors Are Equal: Learning Text Generation Metrics Using Stratified Error Synthesis.” In Findings of the Association for Computational Linguistics: EMNLP 2022, 6559–74. https://aclanthology.org/2022.findings-emnlp.489.
  4. Fomicheva, Marina, Shuo Sun, Lisa Yankovskaya, Frédéric Blain, Francisco Guzmán, Mark Fishel, Nikolaos Aletras, Vishrav Chaudhary, and Lucia Specia. 2020. “Unsupervised Quality Estimation for Neural Machine Translation.” Transactions of the Association for Computational Linguistics 8: 539–55. https://aclanthology.org/2020.tacl-1.35.
  5. Zhang*, Tianyi, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. “BERTScore: Evaluating Text Generation with BERT,” ICLR 2020. https://openreview.net/forum?id=SkeHuCVFDr.
  6. Thibault Sellam, Dipanjan Das, Ankur Parikh. BLEURT: Learning Robust Metrics for Text Generation, ACL 2020.
  7. Ricardo Rei, Craig Stewart, Ana C Farinha, Alon Lavie. COMET: A Neural Framework for MT Evaluation, EMNLP 2020.

Additional Reading

  1. Wang, Xiaohui, Ying Xiong, Yang Wei, Mingxuan Wang, and Lei Li. 2021. “LightSeq: A High Performance Inference Library for Transformers.” In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers, 113–20. https://aclanthology.org/2021.naacl-industry.15.
  2. Zhao, Chengqi, Mingxuan Wang, Qianqian Dong, Rong Ye, and Lei Li. 2021. “NeurST: Neural Speech Translation Toolkit.” In Proc. Of ACL, 55–62. https://aclanthology.org/2021.acl-demo.7.
  3. Artetxe, Mikel, and Holger Schwenk. 2019. “Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond.” Transactions of the Association for Computational Linguistics 7: 597–610. https://aclanthology.org/Q19-1038.
  4. Bahdanau, Dzmitry, Kyunghyun Cho, and Yoshua Bengio. 2015. “Neural Machine Translation by Jointly Learning to Align and Translate.” In Proc. Of ICLR, edited by Yoshua Bengio and Yann LeCun. http://arxiv.org/abs/1409.0473.
  5. Bapna, Ankur, and Orhan Firat. 2019. “Simple, Scalable Adaptation for Neural Machine Translation.” In Proc. Of EMNLP, 1538–48. https://aclanthology.org/D19-1165.
  6. Di Gangi, Mattia A., Roldano Cattoni, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2019. “MuST-C: A Multilingual Speech Translation Corpus.” In Proc. Of NAACL-HLT, 2012–17. https://aclanthology.org/N19-1202.
  7. Conneau, Alexis, and Guillaume Lample. 2019. “Cross-Lingual Language Model Pretraining.” In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, edited by Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d’Alché-Buc, Emily B. Fox, and Roman Garnett, 7057–67. https://proceedings.neurips.cc/paper/2019/hash/c04c19c2c2474dbf5f7ac4372c5b9af1-Abstract.html.
  8. Conneau, Alexis, Shijie Wu, Haoran Li, Luke Zettlemoyer, and Veselin Stoyanov. 2020. “Emerging Cross-Lingual Structure in Pretrained Language Models.” In Proc. Of ACL, 6022–34. https://aclanthology.org/2020.acl-main.536.
  9. Dong, Linhao, Shuang Xu, and Bo Xu. 2018. “Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition.” In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2018, Calgary, AB, Canada, April 15-20, 2018, 5884–88. https://doi.org/10.1109/ICASSP.2018.8462506.
  10. Dalvi, Fahim, Nadir Durrani, Hassan Sajjad, and Stephan Vogel. 2018. “Incremental Decoding and Training Methods for Simultaneous Translation in Neural Machine Translation.” In Proc. Of NAACL-HLT, 493–99. https://aclanthology.org/N18-2079.
  11. Elbayad, Maha, Laurent Besacier, and Jakob Verbeek. 2020. “Efficient Wait-k Models for Simultaneous Machine Translation.” In Proc. Of INTERSPEECH, edited by Helen Meng, Bo Xu, and Thomas Fang Zheng, 1461–65. https://doi.org/10.21437/Interspeech.2020-1241.
  12. Firat, Orhan, Kyunghyun Cho, and Yoshua Bengio. 2016. “Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism.” In Proc. Of NAACL-HLT, 866–75. https://aclanthology.org/N16-1101.
  13. Arivazhagan, Naveen, Ankur Bapna, Orhan Firat, Dmitry Lepikhin, Melvin Johnson, Maxim Krikun, Mia Xu Chen, et al. 2019. “Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges.” ArXiv Preprint abs/1907.05019. https://arxiv.org/abs/1907.05019.
  14. Saxon, Michael, Samridhi Choudhary, Joseph P. McKenna, and Athanasios Mouchtaris. 2021. “End-to-End Spoken Language Understanding for Generalized Voice Assistants.” In Proc. Of INTERSPEECH, edited by Hynek Hermansky, Honza Cernocký, Lukás Burget, Lori Lamel, Odette Scharenborg, and Petr Motlı́cek, 4738–42. https://doi.org/10.21437/Interspeech.2021-1826.
  15. Gu, Jiatao, James Bradbury, Caiming Xiong, Victor O. K. Li, and Richard Socher. 2018. “Non-Autoregressive Neural Machine Translation.” In Proc. Of ICLR. https://openreview.net/forum?id=B1l8BtlCb.
  16. He, Xiaodong, Li Deng, and Alex Acero. 2011. “Why Word Error Rate Is Not a Good Metric for Speech Recognizer Training for the Speech Translation Task?” In Proc. Of ICASSP, 5632–35. IEEE.
  17. Hu, Junjie, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, and Melvin Johnson. 2020. “XTREME: A Massively Multilingual Multi-Task Benchmark for Evaluating Cross-Lingual Generalisation.” In Proc. Of ICML, 119:4411–21. Proceedings of Machine Learning Research. http://proceedings.mlr.press/v119/hu20b.html.
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