# JTubeSpeech: corpus of Japanese speech collected from YouTube for speech recognition and speaker verification

arXiv: https://arxiv.org/abs/2112.09323 · HTML: https://mlsanity.com/paper/2112.09323/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Dec 2021.

## Built on by (most cited first, 21 of 21)

- [YODAS: Youtube-Oriented Dataset for Audio and Speech](https://mlsanity.com/paper/2406.00899/) (2024)
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- [Self-supervised Adaptive Pre-training of Multilingual Speech Models for Language and Dialect Identification](https://mlsanity.com/paper/2312.07338/) (2023)
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- [Whisper-Based Speech Transcription from Videos Across Multiple Languages for Cross-Cultural Understanding](https://mlsanity.com/paper/2609.11772/) (2026)

## Abstract (arXiv)

In this paper, we construct a new Japanese speech corpus called "JTubeSpeech." Although recent end-to-end learning requires large-size speech corpora, open-sourced such corpora for languages other than English have not yet been established. In this paper, we describe the construction of a corpus from YouTube videos and subtitles for speech recognition and speaker verification. Our method can automatically filter the videos and subtitles with almost no language-dependent processes. We consistently employ Connectionist Temporal Classification (CTC)-based techniques for automatic speech recognition (ASR) and a speaker variation-based method for automatic speaker verification (ASV). We build 1) a large-scale Japanese ASR benchmark with more than 1,300 hours of data and 2) 900 hours of data for Japanese ASV.