k-washi / jtubespeech

JTubeSpeech: Corpus of Japanese speech collected from YouTube

This repository provides 1) a list of YouTube videos with Japanese subtitles (JTubeSpeech), 2) scripts for making new lists of new languages, and 3) tiny lists for other languages.

Description

data/{lang}/{YYYYMM}.csv lists as follows. See step4 for download.

	videoid	auto	sub	channelid
0	0017RsBbUHk	True	True	UCTW2tw0Mhho72MojB1L48IQ
1	00PqfZgiboc	False	True	UCzoghTgl4dvIW9GZF6UC-BA
---	---	---	---	---

• lang: Language ID (ja [Japanese], en [English], ...)
• YYYYMM: Year and month when we collect data
• videoid: YouTube video ID. Its YouTube page is https://www.youtube.com/watch?v={videoid}.
• auto: The video has an automatic subtitle or not.
• sub: The video has a manual (i.e., human-generated) subtitle or not.
• channelid: YouTube Channel ID. Its YouTube page is https://www.youtube.com/channel/{channelid}.

Statistics

lang	filename (data/)	#videos-sub-true	#videos-auto-true
ja	ja/202103.csv	110,000 (10,000 hours)	4,960,000
en	en/202108_middle.csv	739543	667555
	en/202108_tiny.csv	74227	65570
ru	ru/202203_middle.csv	258222	349388
	ru/202108_tiny.csv	39890	46061
de	de/202203_middle.csv	194468	527993
	de/202108_tiny.csv	30727	66954
fr	fr/202203_middle.csv	164261	524261
	fr/202108_tiny.csv	25371	70466
ar	ar/202203_middle.csv	158568	311697
	ar/202108_tiny.csv	31993	42649
th	th/202203_middle.csv	154416	250417
	th/202108_tiny.csv	40886	26907
tr	tr/202203_middle.csv	154213	494187
	tr/202108_tiny.csv	27317	68079
hi	hi/202203_middle.csv	132175	172565
	hi/202108_tiny.csv	34034	31439
zh	zh/202108_middle.csv	126271	23387
	zh/202108_tiny.csv	63126	23387
id	id/202203_middle.csv	105334	447836
	id/202108_tiny.csv	18086	72760
el	el/202203_middle.csv	96436	156445
	el/202108_tiny.csv	25947	26735
pt	pt/202203_middle.csv	90600	436425
	pt/202108_tiny.csv	11692	48974
da	da/202203_middle.csv	86027	421190
	da/202108_tiny.csv	18779	62094
bn	bn/202203_middle.csv	75371	303335
	bn/202108_tiny.csv	16315	57112
fi	fi/202203_middle.csv	68571	347307
	fi/202108_tiny.csv	15561	50626
ta	ta/202203_middle.csv	66923	89209
	ta/202108_tiny.csv	21860	26120
hu	hu/202203_middle.csv	64792	351426
	hu/202108_tiny.csv	13154	49237
uk	uk/202203_middle.csv	55098	283741
	uk/202108_tiny.csv	9103	36392
fa	fa/202203_middle.csv	54165	203794
	fa/202108_tiny.csv	10482	24102
ur	ur/202203_middle.csv	47426	177232
	ur/202108_tiny.csv	10917	26503
az	az/202203_middle.csv	42906	272895
	az/202108_tiny.csv	11188	52025
te	te/202203_middle.csv	41478	110521
	te/202108_tiny.csv	11929	24444
ka	ka/202203_middle.csv	38199	158179
	ka/202108_tiny.csv	10395	23914
ml	ml/202203_middle.csv	35477	249624
	ml/202108_tiny.csv	9080	42359
be	be/202203_middle.csv	33935	227854
	be/202108_tiny.csv	7622	37739
is	is/202203_middle.csv	32272	159506
	is/202108_tiny.csv	10632	38268
kk	kk/202203_middle.csv	26021	148230
	kk/202108_tiny.csv	6917	26163
ga	ga/202203_middle.csv	22177	131863
	ga/202108_tiny.csv	9058	51411
ky	ky/202203_middle.csv	20583	150884
	ky/202108_tiny.csv	7241	42027
tg	tg/202203_middle.csv	15451	135276
	tg/202108_tiny.csv	5491	40244

Contributors

• Shinnosuke Takamichi (The University of Tokyo, Japan) [main contributor]
• Ludwig Kürzinger (Technical University of Munich, Germany)
• Takaaki Saeki (The University of Tokyo, Japan)
• Sayaka Shiota (Tokyo Metropolitan University, Japan)
• Shinji Watanabe (Carnegie Mellon University, USA)

Scripts for data collection

scripts/*.py are scripts for data collection from YouTube. Since processes of the scripts are language independent, users can collect data of their favorite languages. youtube-dl and ffmpeg are required.

step1: making search words

The script scripts/make_search_word.py downloads the wikipedia dump file and finds words for searching videos. {lang} is the language code, e.g., ja (Japanese) and en (English).

$ python scripts/make_search_word.py {lang}

step2: obtaining video IDs

The script scripts/obtain_video_id.py obtains YouTube video IDs by searching by words. {filename_word_list} is a word list file made in step1. After this step, the process will take a long time. It is recommended to split the files (e.g., {filename_word_list}) and run them in parallel.

$ python scripts/obtain_video_id.py {lang} {filename_word_list}

step3: checking if subtitles are available

The script scripts/retrieve_subtitle_exists.py retrieves whether the video has subtitles or not. {filename_videoid_list} is a videoID list file made in step2. This process will make a CSV file.

$ python scripts/retrieve_subtitle_exists.py {lang} {filename_videoid_list}

step4: downloading videos with manual subtitles

The script scripts/download_video.py downloads audio and manual subtitles. Note that, this process requires a very large amount of storage.{filename_subtitle_list} is a subtitle list file made in step3. The audio and subtitles will be saved in video/{lang}/wav16k and video/{lang}/txt, respectively.

$ python scripts/download_video.py {lang} {filename_subtitle_list}

step5 (ASR): alignment and scoring

Subtitles are not always correctly aligned with the audio and in some cases, subtitles not fit to the audio. The script scripts/align.py aligns subtitles and audio with CTC segmentation using an ESPnet 2 ASR model:

$ python scripts/align.py {asr_train_config} {asr_model_file} {wavdir} {txtdir} {output_dir}

The result is written into a segments file segments.txt and a log file segments.log in the output directory. Using the segments file, bad utterances or audio files can be sorted-out:

min_confidence_score=-0.3
awk -v ms=${min_confidence_score} '{ if ($5 > ms) {print} }' ${output_dir}/segments.txt

step5 (ASV): speaker variation scoring

There are three types of videos: text-to-speech (a.k.a., TTS) video, single-speaker (i.e., monologue) video, and multi-speaker (e.g., dialogue) video. The script scripts/xxx.py obtains scores of speaker variation within a video to classify videos into three types.

$ python scripts/xxx.py

Reference

• coming soon

Link

• youtube-dl
• Other corpora by main contributor

Update

• Aug. 2021: first update ({lang}/*_tiny.csv)
• Jan. 2022: add mid-size data ({lang}/*_middile.csv)