cs.SDMar 2, 2026

VietSuperSpeech: A Large-Scale Vietnamese Conversational Speech Dataset for ASR Fine-Tuning in Chatbot, Customer Support, and Call Center Applications

Authors: Loan Do, Thanh Ngoc Nguyen, Thanh Pham, Vinh Do, Hien Nguyen, Charlotte Nguyen

Organizations: FPT University · Phuong Hai JSC

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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 https://huggingface.co/datasets/thanhnew2001/VietSuperSpeech.

Figures & tables

SplitUtterancesDuration (hours)Proportion
Train46,822240.6789.0%
Dev/Test5,20126.7211.0%
Total52,023267.39100%
Table 1: VietSuperSpeech dataset statistics.
DatasetHoursTrans.DomainAccessConversational
VIVOS ( Luong and Vu, 2016 )15ManualRead speechOpen×
FOSD/FPTVIET ( FPT Technology Research Institute, 2020 )∼\sim 25ManualRead speechOpen×
FLEURS (vi) ( Conneau et al., 2022 )∼\sim 12ManualParallel readOpen×
VLSP2020 ( VLSP Organizing Committee, 2020 )∼\sim 250ManualNews + spontaneousRestrictedPartial
VLSP2021 ( VLSP Organizing Committee, 2021 )∼\sim 280ManualGeneralRestrictedPartial
VLSP2023 ( VLSP Organizing Committee, 2023 )–ManualGeneralRestrictedPartial
Table 2: Comparison of public Vietnamese ASR datasets. “Pseudo” = pseudo-labeled; “Manual” = human-verified; “Crowd” = crowd-sourced. The “Conversational” column indicates whether the corpus specifically targets casual/spontaneous speech registers suitable for chatbot and call-center ASR.
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