Request access to IRIS-Data

Access requests are reviewed manually. Use of the data is subject to the source-specific terms linked below.

Log in or Sign Up to review the conditions and access this dataset content.

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
Downloads last month
240