metadata
pretty_name: SSSL annotations
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).