Automated Speech Recognition in language learning: Potential models, benefits and impact

Autor:	Michael Carrier
Jazyk:	angličtina
Rok vydání:	2017
Předmět:	automated speech recognition asr elt speech-to-speech translation translation software speech synthesis automated assessment Education Philology. Linguistics P1-1091
Zdroj:	Training, Language and Culture, Vol 1, Iss 1, Pp 46-61 (2017)
Druh dokumentu:	article
ISSN:	2520-2073 2521-442X
DOI:	10.29366/2017tlc.1.1.3
Popis:	The study considers Automated Speech Recognition (ASR) in language learning arguing that speech recognition has reached a level of accuracy where it is powering automatic translation and testing. The author considers the impact of ASR technology on language teaching, describes the process of the development of appropriate pedagogical models, and explains how to prepare teachers for their application. The study will give a critical analysis of the pedagogical uses and dangers of ASR technology and address how ASR can be used to automate language assessment.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/87f2b466a84142f39ec14cff38741cc8 Zobrazit plný text záznamu View record in DOAJ