VoisTUTOR corpus: A speech corpus of Indian L2 English learners for pronunciation assessment

Yarra, C and Srinivasan, A and Srinivasa, C and Aggarwal, R and Ghosh, PK (2019) VoisTUTOR corpus: A speech corpus of Indian L2 English learners for pronunciation assessment. In: 2019 22nd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA), 25-27 Oct. 2019, Cebu, Philippines, Philippines.

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Abstract

This paper describes the voisTUTOR corpus, a pronunciation assessment corpus of Indian second language (L2) learners learning English. This corpus consists of 26529 utterances approximately totalling to 14 hours. The recorded data was collected from 16 Indian L2 learners who are from six native languages, namely, Kannada, Telugu, Tamil, Malayalam, Hindi and Gujarati. A total of 1676 unique stimuli were considered for the recording. The stimuli were designed such that they ranged from single word stimuli to multiple word stimuli containing simple, complex and compound sentences. The corpus also consists of ratings representing overall quality on a scale of 0 to 10 for every utterance. In addition to the overall rating, unlike the existing corpora, a binary decision (0 or 1) is provided indicating the quality of the following seven factors, on which overall pronunciation typically depends,-1) intelligibility, 2) phoneme quality, 3) phoneme mispronunciation, 4) syllable stress quality, 5) intonation quality, 6) correctness of pauses and 7) mother tongue influence. A spoken English expert provides the ratings and binary decisions for all the utterances. Furthermore, the corpus also consists of recordings of all the stimuli obtained from a male and a female spoken English expert. Considering factor dependent binary decisions and spoken English experts' recordings, voisTUTOR corpus is unique compared to the existing corpora. To the best of our knowledge, there exists no such corpus for pronunciation assessment in Indian nativity. © 2019 IEEE.

Item Type:	Conference Paper
Publication:	2019 22nd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques, O-COCOSDA 2019
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	cited By 0; Conference of 22nd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques, O-COCOSDA 2019 ; Conference Date: 25 October 2019 Through 27 October 2019; Conference Code:158712
Keywords:	Standardization, Binary decision; Learning English; Mother tongues; Native language; Overall quality; Pronunciation assessment; Second language; Speech corpora, Audio recordings
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	07 Sep 2020 09:37
Last Modified:	07 Sep 2020 09:37
URI:	http://eprints.iisc.ac.in/id/eprint/65263

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