Passer à la navigation principale Passer à la recherche Passer au contenu principal

Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

Résumé

Abstractive community detection is an important spoken language understanding task, whose goal is to group utterances in a conversation according to whether they can be jointly summarized by a common abstractive sentence. This paper provides a novel approach to this task. We first introduce a neural contextual utterance encoder featuring three types of self-attention mechanisms. We then train it using the siamese and triplet energy-based meta-architectures. Experiments on the AMI corpus show that our system outperforms multiple energy-based and non-energy based baselines from the state-of-the-art. Code and data are publicly available.

langue originaleAnglais
titreProceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, AACL-IJCNLP 2020
rédacteurs en chefKam-Fai Wong, Kevin Knight, Hua Wu
EditeurAssociation for Computational Linguistics (ACL)
Pages313-327
Nombre de pages15
ISBN (Electronique)9781952148910
Les DOIs
étatPublié - 1 janv. 2020
Modification externeOui
Evénement1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, AACL-IJCNLP 2020 - Virtual, Online, Chine
Durée: 4 déc. 20207 déc. 2020

Série de publications

NomProceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, AACL-IJCNLP 2020

Une conférence

Une conférence1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, AACL-IJCNLP 2020
Pays/TerritoireChine
La villeVirtual, Online
période4/12/207/12/20

Empreinte digitale

Examiner les sujets de recherche de « Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation