IRIS-Data
IRIS-Data is a dataset for training instruction-aware speech retrieval models. Each example contains an instruction, a spoken query, a positive document, negative documents, and metadata for the retrieval criteria. The data comes from 14 sources listed below.
Files
| File | Contents |
|---|---|
train.jsonl |
890,278 training examples |
val.jsonl |
9,653 validation examples |
audio/audio-*.tar |
391,468 WAV recordings in 34 archives |
The WAV files are not resampled or re-encoded for this release.
Download
After access is approved, download with your authenticated Hugging Face account:
hf download lca0503/IRIS-Data --repo-type dataset --local-dir IRISData
for archive in IRISData/audio/audio-*.tar; do
tar -xf "$archive" -C IRISData
done
Extraction creates IRISData/audio/<id>.wav.
Audio paths in both JSONL files are relative to IRISData.
Example format
| Field | Description |
|---|---|
instruction |
Retrieval instruction |
spoken_query |
Relative path to the query audio |
positive_document |
Relative path to the positive audio |
negative_documents |
List of relative paths to negative audio |
select_criteria |
Criteria for selecting positive and negative documents |
spoken_query_metadata |
Query metadata |
positive_document_metadata |
Positive document metadata |
negative_documents_metadata |
Metadata for each negative document |
source |
Source dataset identifier |
Metadata includes speaker, gender, emotion, accent, sentiment, environmental_sound, dialogue_id, topic_id, and text.
Missing attributes are null.
Sources and terms
Each source keeps its license and permission requirements. Access to IRIS-Data does not replace those requirements. See the source pages below for terms and attribution.
| Source identifier | Source |
|---|---|
crema_d |
CREMA-D |
emns |
EMNS |
emov_db |
EmoV-DB |
esd |
Emotional Speech Dataset |
l2arctic |
L2-ARCTIC |
librispeech_c |
LibriSpeech-C recipe, LibriSpeech, and MS-SNSD |
meld |
MELD |
msp_improve |
MSP-IMPROV |
multidialog |
MultiDialog |
spokenwoz |
SpokenWOZ |
synthetic |
MS MARCO triplets from sentence-transformers/msmarco-bm25, synthesized with Gemini 2.5 Pro TTS, Gemini 3.1 Flash TTS, and Qwen3 TTS; background sounds from UrbanSound8K |
urbansound8k |
UrbanSound8K |
vocalsound |
VocalSound |
voxceleb1 |
VoxCeleb1 |
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