| --- |
| pretty_name: IRIS-Data |
| language: |
| - en |
| license: other |
| license_name: source-specific-terms |
| license_link: https://huggingface.co/datasets/lca0503/IRIS-Data#sources-and-terms |
| size_categories: |
| - 100K<n<1M |
| tags: |
| - audio |
| - speech |
| - retrieval |
| - instruction-aware-retrieval |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: train.jsonl |
| - split: validation |
| path: val.jsonl |
| extra_gated_heading: Request access to IRIS-Data |
| extra_gated_description: Access requests are reviewed manually. Use of the data is subject to the source-specific terms linked below. |
| extra_gated_button_content: Request access |
| --- |
| |
| # IRIS-Data |
|
|
| IRIS (Instruction-Aware Retrieval for Speech) 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 describing the retrieval criteria. |
|
|
| ## Files |
|
|
| | File | Contents | |
| | --- | --- | |
| | `train.jsonl` | 890,278 training examples. | |
| | `val.jsonl` | 9,653 validation examples. | |
| | `audio/audio-*.tar` | 391,468 WAV recordings, packaged in shards for download. | |
|
|
| Extracting the audio archives creates `audio/<id>.wav`, matching the relative paths in both JSONL files. The WAV files are preserved without resampling or re-encoding. |
|
|
| ## Example format |
|
|
| | Field | Description | |
| | --- | --- | |
| | `instruction` | The retrieval instruction. | |
| | `spoken_query` | Relative path to the query recording. | |
| | `positive_document` | Relative path to a positive recording. | |
| | `negative_documents` | List of relative paths to negative recordings. | |
| | `select_criteria` | The criteria used to select the positive and negative documents. | |
| | `spoken_query_metadata` | Metadata for the query. | |
| | `positive_document_metadata` | Metadata for the positive document. | |
| | `negative_documents_metadata` | Metadata for the negative documents. | |
| | `source` | The source dataset identifier. | |
|
|
| Metadata fields include `speaker`, `gender`, `emotion`, `accent`, `sentiment`, `environmental_sound`, `dialogue_id`, `topic_id`, and `text`. Unavailable attributes are represented by `null`. |
|
|
| ## Download |
|
|
| After access is approved, download the files using an authenticated Hugging Face account: |
|
|
| ```bash |
| 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 |
| ``` |
|
|
| Resolve the audio paths relative to the downloaded `IRISData` directory. |
|
|
| ## Sources and terms |
|
|
| Source materials retain their applicable licenses and permission conditions. Access to this repository does not replace source-specific obligations. Refer to the official source pages below for their terms and attribution requirements. |
|
|
| | Source identifier | Source | |
| | --- | --- | |
| | `crema_d` | [CREMA-D](https://github.com/CheyneyComputerScience/CREMA-D) | |
| | `emns` | [EMNS](https://www.openslr.org/136/) | |
| | `emov_db` | [EmoV-DB](https://github.com/numediart/EmoV-DB) | |
| | `esd` | [Emotional Speech Dataset](https://github.com/HLTSingapore/Emotional-Speech-Data) | |
| | `l2arctic` | [L2-ARCTIC](https://psi.engr.tamu.edu/l2-arctic-corpus/) | |
| | `librispeech_c` | [LibriSpeech-C recipe](https://github.com/hhhaaahhhaa/ASR-TTA), [LibriSpeech](https://www.openslr.org/12/), and [MS-SNSD](https://github.com/microsoft/MS-SNSD) | |
| | `meld` | [MELD](https://github.com/declare-lab/MELD) | |
| | `msp_improve` | [MSP-IMPROV](https://lab-msp.com/MSP/MSP-Improv.html) | |
| | `multidialog` | [MultiDialog](https://huggingface.co/datasets/IVLLab/MultiDialog) | |
| | `spokenwoz` | [SpokenWOZ](https://spokenwoz.github.io/SpokenWOZ-github.io/) | |
| | `synthetic` | [MS MARCO](https://microsoft.github.io/msmarco/) triplets from [sentence-transformers/msmarco-bm25](https://huggingface.co/datasets/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](https://zenodo.org/records/1203745) | |
| | `vocalsound` | [VocalSound](https://github.com/YuanGongND/vocalsound) | |
| | `voxceleb1` | [VoxCeleb1](https://www.robots.ox.ac.uk/~vgg/data/voxceleb/vox1.html) | |
|
|
