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

2021/04/03 by Junbo Zhang, Zhang, Junbo, Zhiwen Zhang +15 · 11 citations
Computer Science · Psychology · #Audio and Speech Processing (eess.AS) #Computation and Language (cs.CL) #FOS: Computer and information sciences #FOS: Electrical engineering #Phonetics and Phonology Research #Sound (cs.SD) #Speech Recognition and Synthesis #Speech and dialogue systems #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2104.01378

openalex publication_date 2021/04/03 · openalex created_date 2021/04/13 · openalex updated_date 2026/07/28

Abstract

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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• MuFFIN: Multifaceted Pronunciation Feedback Model with Interactive Hierarchical Neural Modeling
• Multi-task Pretraining for Enhancing Interpretable L2 Pronunciation Assessment
• Fine-Tuning Large Multimodal Models for Automatic Pronunciation Assessment
• Read to Hear: A Zero-Shot Pronunciation Assessment Using Textual Descriptions and LLMs
• LLaSO: A Foundational Framework for Reproducible Research in Large Language and Speech Model
• Cryfish: On deep audio analysis with Large Language Models
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• Opportunities and Challenges of LLMs in Education: An NLP Perspective

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