  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.
