Vietnamese Automatic Speech Recognition: A Revisit

• URL: http://arxiv.org/abs/2603.14779v1
• Date: Mon, 16 Mar 2026 03:23:54 GMT
• Title: Vietnamese Automatic Speech Recognition: A Revisit
• Abstract summary: We propose a novel data aggregation and preprocessing pipeline to construct high-quality ASR datasets from diverse, potentially noisy, open-source sources.<n>Our pipeline incorporates rigorous processing steps to ensure data diversity, balance, and the inclusion of crucial features like word-level timestamps.<n>We demonstrate the effectiveness of our methodology by applying it to Vietnamese, resulting in a unified, high-quality 500-hour dataset.
• Score: 14.144721540922363
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Automatic Speech Recognition (ASR) performance is heavily dependent on the availability of large-scale, high-quality datasets. For low-resource languages, existing open-source ASR datasets often suffer from insufficient quality and inconsistent annotation, hindering the development of robust models. To address these challenges, we propose a novel and generalizable data aggregation and preprocessing pipeline designed to construct high-quality ASR datasets from diverse, potentially noisy, open-source sources. Our pipeline incorporates rigorous processing steps to ensure data diversity, balance, and the inclusion of crucial features like word-level timestamps. We demonstrate the effectiveness of our methodology by applying it to Vietnamese, resulting in a unified, high-quality 500-hour dataset that provides a foundation for training and evaluating state-of-the-art Vietnamese ASR systems. Our project page is available at https://github.com/qualcomm-ai-research/PhoASR.

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