speechocean762: An Open-Source Non-native English Speech Corpus For Pronunciation Assessment

Daniel Povey; Junbo Zhang; Ke Li; Qiong Song; Yongqing Wang; Yujun Wang; Yukai Huang; Zhiwen Zhang; Zhiyong Yan

arxiv: 2104.01378 · v2 · pith:AQPDFIPHnew · submitted 2021-04-03 · 💻 cs.CL · cs.SD· eess.AS

speechocean762: An Open-Source Non-native English Speech Corpus For Pronunciation Assessment

Junbo Zhang , Zhiwen Zhang , Yongqing Wang , Zhiyong Yan , Qiong Song , Yukai Huang , Ke Li , Daniel Povey

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Yujun Wang

This is my paper

classification 💻 cs.CL cs.SDeess.AS

keywords corpusassessmentpronunciationspeechbaselineenglishnon-nativeopen-source

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This paper introduces a new open-source speech corpus named "speechocean762" designed for pronunciation assessment use, consisting of 5000 English utterances from 250 non-native speakers, where half of the speakers are children. Five experts annotated each of the utterances at sentence-level, word-level and phoneme-level. A baseline system is released in open source to illustrate the phoneme-level pronunciation assessment workflow on this corpus. This corpus is allowed to be used freely for commercial and non-commercial purposes. It is available for free download from OpenSLR, and the corresponding baseline system is published in the Kaldi speech recognition toolkit.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

Light-weight Pronunciation Assessment via Discrete Speech Token Surprisal
cs.CL 2026-06 unverdicted novelty 5.0

A framework using native-only trained discrete token surprisal and DTW alignment features improves pronunciation assessment PCC to 0.66 on SpeechOcean762, approaching supervised performance.