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Using Google Voice Typing to Automatically Assess Pronunciation

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Title: Using Google Voice Typing to Automatically Assess Pronunciation
Language: English
Authors: Johnson, Carol (ORCID 0000-0001-6859-6566), Cardoso, Walcir (ORCID 0000-0001-6376-185X), Zuercher, Beau, Brannen, Kathleen, Springer, Suzanne
Source: Research-publishing.net. 2022.
Availability: Research-publishing.net. La Grange des Noyes, 25110 Voillans, France. e-mail: info@research-publishing.net; Web site: http://research-publishing.net
Peer Reviewed: Y
Page Count: 6
Publication Date: 2022
Document Type: Speeches/Meeting Papers
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Teaching Methods, Computer Software, Pronunciation, Second Language Learning, Second Language Instruction, English (Second Language), Audio Equipment, Language Tests, Student Placement, Student Evaluation, Evaluators, Comparative Analysis, Correlation, Scores, Test Use, Undergraduate Students, Speech Communication, Foreign Countries
Geographic Terms: Canada
Abstract: This study examined the use of a popular Automatic Speech Recognition (ASR), Google Voice Typing (GVT), to automatically assess English as second language pronunciation. It aimed to answer the following question: What is the relationship between GVT-rated scores and human-rated scores? To answer this question, we compared audio recordings of 56 oral placement tests, rated by both human raters and GVT. Our results indicate that GVT scores strongly correlated with human-rater scores, indicating that this non-customizable ASR technology could be leveraged to increase the test usefulness of language placement tests. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]
Abstractor: As Provided
Entry Date: 2023
Accession Number: ED625189
Database: ERIC
FullText Text:
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  Data: <searchLink fieldCode="AR" term="%22Johnson%2C+Carol%22">Johnson, Carol</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6859-6566">0000-0001-6859-6566</externalLink>)<br /><searchLink fieldCode="AR" term="%22Cardoso%2C+Walcir%22">Cardoso, Walcir</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6376-185X">0000-0001-6376-185X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Zuercher%2C+Beau%22">Zuercher, Beau</searchLink><br /><searchLink fieldCode="AR" term="%22Brannen%2C+Kathleen%22">Brannen, Kathleen</searchLink><br /><searchLink fieldCode="AR" term="%22Springer%2C+Suzanne%22">Springer, Suzanne</searchLink>
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  Data: This study examined the use of a popular Automatic Speech Recognition (ASR), Google Voice Typing (GVT), to automatically assess English as second language pronunciation. It aimed to answer the following question: What is the relationship between GVT-rated scores and human-rated scores? To answer this question, we compared audio recordings of 56 oral placement tests, rated by both human raters and GVT. Our results indicate that GVT scores strongly correlated with human-rater scores, indicating that this non-customizable ASR technology could be leveraged to increase the test usefulness of language placement tests. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.]
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  Data: ED625189
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      – Text: English
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        PageCount: 6
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      – SubjectFull: Teaching Methods
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      – SubjectFull: Computer Software
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      – SubjectFull: Pronunciation
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      – SubjectFull: Second Language Learning
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      – SubjectFull: Audio Equipment
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      – SubjectFull: Language Tests
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      – SubjectFull: Student Placement
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      – SubjectFull: Student Evaluation
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      – SubjectFull: Speech Communication
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Canada
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      – TitleFull: Using Google Voice Typing to Automatically Assess Pronunciation
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