@inproceedings{kollar-etal-2018-alexa,
title = "The {A}lexa Meaning Representation Language",
author = "Kollar, Thomas and
Berry, Danielle and
Stuart, Lauren and
Owczarzak, Karolina and
Chung, Tagyoung and
Mathias, Lambert and
Kayser, Michael and
Snow, Bradford and
Matsoukas, Spyros",
editor = "Bangalore, Srinivas and
Chu-Carroll, Jennifer and
Li, Yunyao",
booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)",
month = jun,
year = "2018",
address = "New Orleans - Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N18-3022",
doi = "10.18653/v1/N18-3022",
pages = "177--184",
abstract = "This paper introduces a meaning representation for spoken language understanding. The Alexa meaning representation language (AMRL), unlike previous approaches, which factor spoken utterances into domains, provides a common representation for how people communicate in spoken language. AMRL is a rooted graph, links to a large-scale ontology, supports cross-domain queries, fine-grained types, complex utterances and composition. A spoken language dataset has been collected for Alexa, which contains ∼20k examples across eight domains. A version of this meaning representation was released to developers at a trade show in 2016.",
}
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%0 Conference Proceedings
%T The Alexa Meaning Representation Language
%A Kollar, Thomas
%A Berry, Danielle
%A Stuart, Lauren
%A Owczarzak, Karolina
%A Chung, Tagyoung
%A Mathias, Lambert
%A Kayser, Michael
%A Snow, Bradford
%A Matsoukas, Spyros
%Y Bangalore, Srinivas
%Y Chu-Carroll, Jennifer
%Y Li, Yunyao
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans - Louisiana
%F kollar-etal-2018-alexa
%X This paper introduces a meaning representation for spoken language understanding. The Alexa meaning representation language (AMRL), unlike previous approaches, which factor spoken utterances into domains, provides a common representation for how people communicate in spoken language. AMRL is a rooted graph, links to a large-scale ontology, supports cross-domain queries, fine-grained types, complex utterances and composition. A spoken language dataset has been collected for Alexa, which contains ∼20k examples across eight domains. A version of this meaning representation was released to developers at a trade show in 2016.
%R 10.18653/v1/N18-3022
%U https://aclanthology.org/N18-3022
%U https://doi.org/10.18653/v1/N18-3022
%P 177-184
Markdown (Informal)
[The Alexa Meaning Representation Language](https://aclanthology.org/N18-3022) (Kollar et al., NAACL 2018)
ACL
- Thomas Kollar, Danielle Berry, Lauren Stuart, Karolina Owczarzak, Tagyoung Chung, Lambert Mathias, Michael Kayser, Bradford Snow, and Spyros Matsoukas. 2018. The Alexa Meaning Representation Language. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers), pages 177–184, New Orleans - Louisiana. Association for Computational Linguistics.