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

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arxiv 2104.01378 v2 pith:AQPDFIPH submitted 2021-04-03 cs.CL cs.SDeess.AS

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 · ORCID
classification cs.CLcs.SDeess.AS
keywords corpusassessmentpronunciationspeechbaselineenglishnon-nativeopen-source
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 3 Pith papers

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

  1. PRiSM: Benchmarking Phone Realization in Speech Models

    cs.CL 2026-01 conditional novelty 7.0 of 10

    PRiSM benchmarks phone recognition in speech models with intrinsic transcription and extrinsic downstream probes, finding that multilingual training and encoder-CTC architectures perform most consistently while LALMs ...

  2. English Pronunciation Evaluation without Complex Joint Training: LoRA Fine-tuned Speech Multimodal LLM

    cs.CL 2025-09 conditional novelty 6.0 of 10

    LoRA fine-tuning of the Phi-4 multimodal LLM on Speechocean762 yields pronunciation scores and phoneme-level transcripts from a single model, with PCC up to 0.74 for accuracy and PER down to 0.11.

  3. JCAPT: A Joint Modeling Approach for CAPT

    cs.CL 2025-06 conditional novelty 4.0 of 10

    JCAPT, a Mamba-based joint APA and MDD model with phonological features and think tokens, improves mispronunciation detection and several scoring aspects on speechocean762 over JAM.

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