{"id":19932283,"url":"https://github.com/amazon-science/multiatis","last_synced_at":"2025-05-03T11:31:53.610Z","repository":{"id":49807797,"uuid":"301538886","full_name":"amazon-science/multiatis","owner":"amazon-science","description":"Data and code for the paper \"End-to-End Slot Alignment and Recognition for Cross-Lingual NLU\" (Accepted to EMNLP 2020)","archived":false,"fork":false,"pushed_at":"2022-01-13T20:10:08.000Z","size":34,"stargazers_count":24,"open_issues_count":2,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-07T15:11:11.667Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/amazon-science.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-10-05T21:01:59.000Z","updated_at":"2024-11-19T11:55:47.000Z","dependencies_parsed_at":"2022-09-15T18:03:05.373Z","dependency_job_id":null,"html_url":"https://github.com/amazon-science/multiatis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amazon-science%2Fmultiatis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amazon-science%2Fmultiatis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amazon-science%2Fmultiatis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amazon-science%2Fmultiatis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/amazon-science","download_url":"https://codeload.github.com/amazon-science/multiatis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252184417,"owners_count":21707953,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-12T23:09:34.996Z","updated_at":"2025-05-03T11:31:53.206Z","avatar_url":"https://github.com/amazon-science.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"## MultiAtis++ Corpus\n\n### Description\n\nThe ATIS (Air Travel Information Services) collection was developed to support the research and development of speech understanding systems [1]. The original English data includes intent and slot annotations, and was later extended to Hindi and Turkish [2]. MultiATIS++ futher extends ATIS to 6 more languages, and hence, covers a total of 9 languages, that is, English, Spanish, German, French, Portuguese, Chinese, Japanese, Hindi and Turkish. These locales  belong to a diverse set of language families- Indo-European, Sino-Tibetan, Japonic and Altaic.\n\nMultiATIS++ corpus has been outsourced to foster further research in the domain of multilingual/cross-lingual natural language understanding.\n\nFor more details, please check the paper:\nXu, W., Haider, B. and Mansour, S., 2020. End-to-End Slot Alignment and Recognition for Cross-Lingual NLU. arXiv preprint arXiv:2004.14353 (https://arxiv.org/abs/2004.14353)\n\n### Accessing MultiAtis++\n\nTo obtain a copy of *MutliAtis++* data, please visit:\nhttps://catalog.ldc.upenn.edu/LDC2021T04\n\nPlease send your queries/comments to multiatis@amazon.com.\n\n### Citation\n\nPlease cite [3] when referring to the MultiATIS++ dataset.\n\n\n## Soft-Align Implementation\n\nImplementation of the *soft-align* method introduced in [3] will be available here, soon.\n\n\n## Security\n\nSee [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.\n\n## License\n\nThis project is licensed under the Apache-2.0 License.\n\n## References\n\n[1] LDC93S5 ATIS2, LDC94S19 ATIS3 Training Data, LDC95S26 ATIS3 Test Data\n\n[2] Shyam Upadhyay, Manaal Faruqui, Gokhan Tur, Dilek Hakkani-Tur, Larry Heck. (Almost) Zero-Shot Cross-Lingual Spoken Language Understanding. IEEE ICASSP 2018.\n\n[3] Weijia Xu, Batool Haider, Saab Mansour. 2020. End-to-End Slot Alignment and Recognition for Cross-Lingual NLU. arXiv preprint arXiv:2004.14353.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famazon-science%2Fmultiatis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Famazon-science%2Fmultiatis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famazon-science%2Fmultiatis/lists"}