Scikit-talk: A toolkit for processing real-world conversational speech data

Andreas Liesenfeld, Gábor Parti, Chu Ren Huang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

We present Scikit-talk, an open-source toolkit for processing collections of real-world conversational speech in Python. First of its kind, the toolkit equips those interested in studying or modeling conversations with an easyto-use interface to build and explore large collections of transcriptions and annotations of talk-in-interaction. Designed for applications in speech processing and Conversational AI, Scikit-talk provides tools to custombuild datasets for tasks such as intent prototyping, dialog flow testing, and conversation design. Its preprocessor module comes with several pre-built interfaces for common transcription formats, which aim to make working across multiple data sources more accessible. The explorer module provides a collection of tools to explore and analyse this data type via string matching and unsupervised machine learning techniques. Scikit-talk serves as a platform to collect and connect different transcription formats and representations of talk, enabling the user to quickly build multilingual datasets of varying detail and granularity. Thus, the toolkit aims to make working with authentic conversational speech data in Python more accessible and to provide the user with comprehensive options to work with representations of talk in appropriate detail for any downstream task. For the latest updates and information on currently supported languages and language resources, please refer to: https://pypi.org/project/scikit-talk/.

Original languageEnglish
Title of host publicationSIGDIAL 2021 - 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference
EditorsHaizhou Li, Gina-Anne Levow, Zhou Yu, Chitralekha Gupta, Berrak Sisman, Siqi Cai, David Vandyke, Nina Dethlefs, Yan Wu, Junyi Jessy Li
PublisherAssociation for Computational Linguistics (ACL)
Pages252-256
Number of pages5
ISBN (Electronic)9781954085817
DOIs
Publication statusPublished - Jul 2021
Event22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2021 - Virtual, Singapore, Singapore
Duration: 29 Jul 202131 Jul 2021

Publication series

NameSIGDIAL 2021 - 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference

Conference

Conference22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2021
Country/TerritorySingapore
CityVirtual, Singapore
Period29/07/2131/07/21

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Modelling and Simulation

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