Blinorot/ALARM-Corpora

---
dataset_info:
features:
- name: audio_description
dtype: string
- name: unique_id_1
dtype: string
- name: unique_id_2
dtype: string
- name: dataset_index
dtype: int64
- name: context
dtype: string
- name: llm_answer_with_context
dtype: string
- name: llm_answer_no_context
dtype: string
- name: dataset_name
dtype: string
splits:
- name: raw_train
num_bytes: 12059336672
num_examples: 6002682
- name: raw_validation
num_bytes: 23524235
num_examples: 4158
- name: train
num_bytes: 10995612354
num_examples: 5447863
- name: validation
num_bytes: 1067155915
num_examples: 554842
download_size: 10539229221
dataset_size: 24145629176
configs:
- config_name: default
data_files:
- split: raw_train
path: data/raw_train-*
- split: raw_validation
path: data/raw_validation-*
- split: train
path: data/train-*
- split: validation
path: data/validation-*
tags:
- audio
- audio-understanding
- LLM
- RLM
size_categories:
- 1M<n<10M
---

# Dataset Card for ALARM-Corpora

## Dataset Summary

This is the dataset used in the [ALARM: Audio-Language Alignment for Reasoning Models](https://arxiv.org/abs/2603.09556) paper.
It consists of Audio Captions and Reasoning Language Model responses rephrased to sound like they were provided by an audio-understanding model.

For more details regarding the dataset and the instructions for obtaining audio files, please refer to our [GitHub](https://github.com/Blinorot/ALARM).

## Dataset Statistics

| Audio Type | # Elements (M) | # Hours (K) | # Unique Prompts (M) |
| ----------- | ------------------ | -------------------- | -------------------- |
| Speech | 2.91 / 2.60 / 0.29 | 9.88 / 8.83 / 0.98 | 1.40 / 1.27 / 0.16 |
| Sound | 2.01 / 1.80 / 0.20 | 5.54 / 4.98 / 0.55 | 0.36 / 0.33 / 0.06 |
| Music | 0.59 / 0.53 / 0.06 | 2.45 / 2.21 / 0.24 | 0.16 / 0.14 / 0.03 |
| Instruction | 0.57 / 0.56 / 0.01 | 1.02 / 1.01 / 0.01 | 0.57 / 0.56 / 0.01 |
| **Total** | 6.08 / 5.49 / 0.56 | 18.89 / 17.03 / 1.78 | 2.49 / 2.30 / 0.26 |

## Citation

If you use this work, please cite:

```bibtex
@article{grinberg2026alarm,
title={ALARM: Audio-Language Alignment for Reasoning Models},
author={Grinberg, Petr and Shahmohammadi, Hassan},
journal={arXiv preprint arXiv:2603.09556},
year={2026}
}
```

## License

All captions and metadata preserve the licenses of the original datasets. Our added LLM responses are provided under CC BY-NC 4.0.