From text to talk: Harnessing conversational corpora for humane and 
diversity-aware language technology

Dingemanse, Mark; Liesenfeld, Andreas

doi:10.18653/v1/2022.acl-long.385

アイテム詳細

登録内容を編集ファイル形式で保存

一時保存へ追加

タグ情報を表示リリース履歴を表示詳細要約

公開

会議論文

From text to talk: Harnessing conversational corpora for humane and diversity-aware language technology

MPS-Authors

There are no MPG-Authors in the publication available

External Resource

There are no locators available

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

フルテキスト (公開)

Dingemanse_Liesenfeld_2022_from text to talk.pdf
(出版社版), 2MB

付随資料 (公開)

There is no public supplementary material available

引用

Dingemanse, M., & Liesenfeld, A. (2022). From text to talk: Harnessing conversational corpora for humane and diversity-aware language technology. In S., Muresan, P., Nakov, & A., Villavicencio (Eds.), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (pp. 5614 -5633). Dublin, Ireland: Association for Computational Linguistics.

引用: https://hdl.handle.net/21.11116/0000-000D-047C-4

要旨

Informal social interaction is the primordial home of human language. Linguistically diverse conversational corpora are an important and largely untapped resource for computational linguistics and language technology. Through the efforts of a worldwide language documentation movement, such corpora are increasingly becoming available. We show how interactional data from 63 languages (26 families) harbours insights about turn-taking, timing, sequential structure and social action, with implications for language technology, natural language understanding, and the design of conversational interfaces. Harnessing linguistically diverse conversational corpora will provide the empirical foundations for flexible, localizable, humane language technologies of the future.