Abstract
We introduce VietSuperSpeech, a large-scale Vietnamese automatic speech recognition (ASR) dataset of 52,023 audio-text pairs totaling 267.39 hours, with a distinctive focus on casual conversational speech. Unlike existing Vietnamese ASR corpora that predominantly feature read speech, news narration, or audiobook content, VietSuperSpeech is sourced from four publicly accessible YouTube channels spanning everyday conversation, personal vlogging, overseas Vietnamese community dialogue, and informal commentary - the very speech styles encountered in real-world chatbot, customer support, call center, and hotline deployments. All audio is standardized to 16 kHz mono PCM WAV and segmented into 3-30 second utterances. Transcriptions are generated via pseudo-labeling using the Zipformer-30M-RNNT-6000h model (Nguyen, 2025) deployed through Sherpa-ONNX, pre-trained on 6,000 hours of Vietnamese speech. After quality filtering, the dataset is split into 46,822 training samples (240.67 hours) and 5,201 development/test samples (26.72 hours) with a fixed random seed. The text averages 266 characters per utterance, totaling 13.8 million fully diacritically marked Vietnamese characters. We demonstrate that VietSuperSpeech fills a critical gap in the Vietnamese ASR ecosystem: while corpora such as VLSP2020, VIET_BUD500, VietSpeech, FLEURS, VietMed, Sub-GigaSpeech2-Vi, viVoice, and Sub-PhoAudioBook provide broad coverage of formal and read speech, none specifically targets the casual, spontaneous register indispensable for conversational AI applications. VietSuperSpeech is publicly released at this https URL.
Abstract (translated)
我们介绍了VietSuperSpeech，这是一个包含52,023对音频文本数据、总计267.39小时的大型越南语自动语音识别（ASR）数据集，特别侧重于日常对话中的非正式会话内容。与现有主要收录朗读、新闻播报或有声书内容的越南语ASR语料库不同，VietSuperSpeech的数据来源于四个公开访问的YouTube频道，这些渠道涵盖了日常生活对话、个人博客视频、海外越南社区对话以及非正式评论——这些都是实际应用中聊天机器人、客户支持和呼叫中心会遇到的真实语音风格。所有音频统一标准化为16 kHz单声道PCM WAV格式，并被分割成3到30秒长的片段。 转录文本是通过使用Zipformer-30M-RNNT-6000h模型（Nguyen, 2025）进行伪标签生成，该模型在经过6,000小时越南语语音预训练后部署于Sherpa-ONNX平台。质量过滤之后，数据集被分为46,822个用于训练的样本（总计240.67小时）和5,201个开发/测试样本（共计26.72小时），并采用固定随机种子进行划分。每个语音片段的文本平均长度为266字符，整个数据集包含约1380万完全带音标符号的越南语字符。 我们展示了VietSuperSpeech填补了越南语ASR生态系统中的关键空白：虽然诸如VLSP2020、VIET_BUD500、VietSpeech、FLEURS、VietMed、Sub-GigaSpeech2-Vi、viVoice和Sub-PhoAudioBook等数据集广泛涵盖了正式及朗读语音，但没有一个专门针对非正式、即兴的日常会话场景，而这对于对话型AI应用至关重要。VietSuperSpeech可以在[这里](https://this-url.com)公开获取（原文链接处应填写具体网址）。
URL
https://arxiv.org/abs/2603.01894
