SSSL annotations (Lhotse shar cuts, no audio)
These are the Lhotse shar cuts.NNNNNN.jsonl.gz manifests for the labelled SSSL training and evaluation
data on the Fir cluster. Audio is not included: the recording.*.tar shards were left out. Phone
alignments are in supervisions[].alignment.phone as [symbol (IPA), start, duration, null].
Layout
The layout is {dataset}/{language}.tar, with one tar for each language of a dataset. Inside a tar, the
files keep their source paths: {dataset}_shar/{split}/cuts.*.jsonl.gz for the sssl_data and
speech_test_shar sets, and {dataset}/cuts.*.jsonl.gz for the training corpora. Common Voice keeps its
shard dirs, commonvoice/{locale}_{locale}_train_N_16k_flac/.
hf download charsiu/sssl-annotations librispeech/en.tar --repo-type dataset --local-dir .
Statistics
"Hours" is the summed cut duration. "Cuts with phone alignment" counts the cuts that have a non-empty
alignment.phone tier. The rest are text only, and FLEURS has no alignments at all.
| dataset | languages | tars | cuts | hours | cuts with phone alignment | source root on Fir |
|---|---|---|---|---|---|---|
wenetspeech |
zh |
1 | 14,509,578 | 9,870.0 | 14,509,578 (100.0%) | speech_alignment_neo_shar |
commonvoice |
59 (see folder) | 59 | 5,514,602 | 8,144.2 | 5,514,602 (100.0%) | speech_alignment_shar |
peoples_speech |
en |
1 | 1,496,210 | 5,874.9 | 1,496,210 (100.0%) | speech_alignment_neo_shar |
libriheavy_medium |
en |
1 | 1,101,040 | 4,533.3 | 1,099,957 (99.9%) | speech_alignment_neo_shar |
mls_german_train |
de |
1 | 469,942 | 1,966.5 | 469,443 (99.9%) | speech_alignment_neo_shar |
dutch_mls |
nl |
1 | 374,287 | 1,554.2 | 190,301 (50.8%) | speech_alignment_neo_shar |
mls_french_train |
fr |
1 | 258,213 | 1,076.6 | 257,910 (99.9%) | speech_alignment_neo_shar |
librispeech |
en |
1 | 286,514 | 971.7 | 286,514 (100.0%) | sssl_data |
mls_spanish_train |
es |
1 | 220,701 | 917.7 | 217,899 (98.7%) | speech_alignment_neo_shar |
fleurs |
77 (see folder) | 77 | 159,853 | 544.0 | 0 (0.0%) | sssl_data |
italian_mls_ipa |
it |
1 | 59,623 | 247.4 | 58,286 (97.8%) | speech_alignment_neo_shar |
mls_portuguese_train |
pt |
1 | 37,533 | 161.0 | 37,123 (98.9%) | speech_alignment_neo_shar |
commonphone |
de, en, es, fr, it, ru |
6 | 76,307 | 116.5 | 76,307 (100.0%) | sssl_data |
mls_polish_train |
pl |
1 | 25,043 | 103.6 | 24,772 (98.9%) | speech_alignment_neo_shar |
russian_librispeech |
ru |
1 | 54,472 | 92.8 | 54,445 (100.0%) | speech_alignment_neo_shar |
aishell3 |
zh |
1 | 88,035 | 85.6 | 88,035 (100.0%) | speech_alignment_neo_shar |
zeroth_korean |
ko |
1 | 22,720 | 52.9 | 22,640 (99.6%) | speech_alignment_neo_shar |
wiktionary |
ces, deu, eng, fra, pol, rus, swe, ukr |
8 | 99,596 | 40.5 | 99,596 (100.0%) | sssl_data |
thchs30 |
zh |
1 | 13,388 | 34.2 | 13,388 (100.0%) | sssl_data |
uk_ireland_english |
en |
1 | 17,877 | 31.3 | 17,869 (100.0%) | speech_alignment_neo_shar |
google_spanish |
es |
1 | 18,698 | 29.8 | 18,698 (100.0%) | speech_alignment_neo_shar |
multilingual_keywords |
cs, de, en, es, ja, pt, tr |
7 | 249,433 | 26.9 | 249,422 (100.0%) | speech_alignment_neo_shar |
gtimit_treebank |
en |
1 | 11,993 | 24.1 | 11,993 (100.0%) | sssl_data |
doreco |
38 (see folder) | 38 | 14,369 | 14.8 | 14,369 (100.0%) | speech_test_shar |
buckeye |
en |
1 | 19,086 | 12.6 | 19,086 (100.0%) | sssl_data |
african_french |
fr |
1 | 10,239 | 12.5 | 10,026 (97.9%) | speech_alignment_neo_shar |
gtimit_simple |
en |
1 | 11,983 | 12.3 | 11,983 (100.0%) | sssl_data |
gtimit_thai |
th |
1 | 6,000 | 11.8 | 6,000 (100.0%) | sssl_data |
media_speech_turkish |
tr |
1 | 2,513 | 10.0 | 2,506 (99.7%) | speech_alignment_neo_shar |
alffa_swahili |
sw |
1 | 10,180 | 9.9 | 1,246 (12.2%) | speech_alignment_neo_shar |
nigerian_english |
en |
1 | 3,359 | 5.8 | 3,359 (100.0%) | speech_alignment_neo_shar |
timit |
en |
1 | 6,300 | 5.4 | 6,300 (100.0%) | sssl_data |
voxangeles |
95 (see folder) | 95 | 5,445 | 1.6 | 5,445 (100.0%) | sssl_data |
| total | 316 | 25,255,132 | 36,596.4 | 24,895,308 (98.6%) |
Notes
- Language codes are each dataset's own: ISO 639-1 (
en,de), Common Voice locales (zh-CN,fy-NL), FLEURS locales (th_th), ISO 639-3 (Wiktionary, VoxAngeles) and Glottocodes (DoReCo). LibriSpeech, TIMIT, Buckeye, gTIMIT simple/treebank and the English training corpora are underen; THCHS-30, AISHELL-3 and WenetSpeech are underzh. - Byte-identical copies, except for VoxAngeles. Its 3 original shards mix 95 languages, so they were split
into one
cuts.000000.jsonl.gzper language, keeping the cut order. - Duplicate copies left out: the
speech_alignment_neo_sharcopies of LibriSpeech, Common Phone and THCHS-30, and thespeech_test_sharcopies of the evaluation sets. They are byte-identical to the files here. - Not included: the unlabelled pretraining corpora (
speech_unsup_shar).
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