Datasets:

ALMData
/

highqualASRsoup

license: other
language:
  - en
task_categories:
  - automatic-speech-recognition
pretty_name: High-quality ASR soup (transcripts and metadata)
size_categories:
  - 1M<n<10M
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/*/*.parquet
  - config_name: common_voice
    data_files:
      - split: train
        path: data/common_voice/*.parquet
  - config_name: spgispeech
    data_files:
      - split: train
        path: data/spgispeech/*.parquet
  - config_name: gigaspeech_audiobook
    data_files:
      - split: train
        path: data/gigaspeech_audiobook/*.parquet
  - config_name: ami
    data_files:
      - split: train
        path: data/ami/*.parquet

highqualASRsoup

Transcripts and metadata of an English ASR training mix built from four public corpora. No audio is included: each row carries the ids needed to fetch the audio from the upstream release.

Subset	Upstream	Rows	Share of rows	Hours	Transcript
`common_voice`	Common Voice English 26.0, train	1,147,340	30.14 %	1,812.4	as released
`spgispeech`	SPGISpeech L, train	1,926,805	50.62 %	4,900.2	as released
`gigaspeech_audiobook`	GigaSpeech L, audiobook-source rows	623,565	16.38 %	650.0	rewritten (see below)
`ami`	AMI IHM, train	108,502	2.85 %	77.9	rewritten (see below)
Total		3,806,212		7,440.5

Transcript refinement

GigaSpeech and AMI ship upper-case transcripts; GigaSpeech also uses symbolic punctuation tokens (<COMMA>, <PERIOD>, ...). For those two subsets every transcript was rewritten into normal written English (casing and punctuation) by gpt-5.6-luna (prompt version 20260907-v2); the upstream transcript is kept in original_text. Common Voice and SPGISpeech transcripts are as released (original_text and text_patch_model are null), except 37 Common Voice rows whose text had been merged with the following TSV record (tab/newline in the field) during the build and was re-read literally from the release's train.tsv.

Example (gigaspeech_audiobook): SIX TOMATOES <PERIOD> → Six tomatoes.

Columns

Column	Meaning
`utt_id`	sha1 of `"
`corpus`	subset name
`id`	upstream utterance id: CV clip file name, SPGISpeech `wav_filename`, GigaSpeech `segment_id`, AMI `audio_id`
`text`	transcript used for training (refined for GigaSpeech / AMI)
`original_text`, `text_patch_model`	upstream transcript and rewrite model (GigaSpeech / AMI only)
`speaker`	CV `client_id`, AMI `speaker_id`, GigaSpeech `speaker` (upstream value, usually `N/A`)
`group`	leakage group for speaker/recording-disjoint splits: CV client, SPGISpeech call, GigaSpeech book (`audio_id`), AMI speaker
`duration_seconds`	from metadata: SPGISpeech WAV size (16 kHz, 16-bit), CV `clip_durations.tsv`, GigaSpeech / AMI `end_time - begin_time`
`begin_time`, `end_time`	segment times in the source recording (GigaSpeech, AMI)
`audio_id`, `meeting_id`, `microphone_id`	upstream recording ids (GigaSpeech book, AMI meeting / headset; CV clip)
`title`, `url`, `source`, `category`, `original_full_path`	GigaSpeech audiobook metadata, as released
`cv_source_dataset`, `wav_filesize`	CV release tag; SPGISpeech WAV size in bytes
`source_shard`, `source_row`	Parquet file and row in the soup build (SPGISpeech, GigaSpeech and AMI file names follow the upstream Hub shard names; Common Voice files are the build's own metadata shards)

Getting the audio

Join on id with the upstream release: Common Voice English 26.0 (clips/<id>), SPGISpeech (kensho/spgispeech, config L, wav_filename), GigaSpeech (speechcolab/gigaspeech, config l, segment_id), AMI (edinburghcstr/ami, config ihm, audio_id).

License

Each subset remains under its upstream license and terms of use: Common Voice (CC0-1.0), AMI (CC BY 4.0), SPGISpeech and GigaSpeech (gated on the Hub; accept their terms there). Use of these transcripts is subject to the same terms.