README.md

---
language:
- en
license: cc-by-nc-4.0
task_categories:
- question-answering
- automatic-speech-recognition
- audio-classification
- audio-text-to-text
dataset_info:
  features:
  - name: transcription_id
    dtype: string
  - name: transcription
    dtype: string
  - name: description
    dtype: string
  - name: intonation
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 48000
  - name: interpretation_id
    dtype: string
  - name: metadata
    struct:
    - name: gender
      dtype: string
    - name: language_code
      dtype: string
    - name: sample_rate_hertz
      dtype: int64
    - name: voice_name
      dtype: string
  - name: possible_answers
    sequence: string
  - name: label
    dtype: int64
  - name: stress_pattern
    struct:
    - name: binary
      sequence: int64
    - name: indices
      sequence: int64
    - name: words
      sequence: string
  - name: audio_lm_prompt
    dtype: string
  splits:
  - name: test
    num_bytes: 87849649.0
    num_examples: 218
  download_size: 67155906
  dataset_size: 87849649.0
tags:
- speech
- stress
- intonation
- audio-reasoning
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
---

# StressTest Evaluation Dataset

This dataset supports the evaluation of models on **Sentence Stress Reasoning (SSR)** and **Sentence Stress Detection (SSD)** tasks, as introduced in our paper:

**[StressTest: Can YOUR Speech LM Handle the Stress?](https://arxiv.org/abs/2505.22765)**

💻 [Code Repository](https://github.com/slp-rl/StressTest) | 🤗 [Model: StresSLM](https://huggingface.co/slprl/StresSLM) | 🤗 [Stress-17k Dataset](https://huggingface.co/datasets/slprl/Stress-17K-raw) 

📃 [Paper](https://huggingface.co/papers/2505.22765) | 🌐 [Project Page](https://pages.cs.huji.ac.il/adiyoss-lab/stresstest/)

---

## 🗂️ Dataset Overview

This dataset includes **218** evaluation samples (split: `test`) with the following features:

* `transcription_id`: Identifier for each transcription sample.
* `transcription`: The spoken text.
* `description`: Description of the interpretation of the stress pattern.
* `intonation`: The stressed version of the transcription.
* `interpretation_id`: Unique reference to the interpretation imposed by the stress pattern of the sentence.
* `audio`: Audio data at 48kHz sampling rate.
* `metadata`: Structured metadata including:

  * `gender`: Speaker gender.
  * `language_code`: Language of the transcription.
  * `sample_rate_hertz`: Sampling rate in Hz.
  * `voice_name`: Voice name.
* `possible_answers`: List of possible interpretations for SSR.
* `label`: Ground truth label for SSR.
* `stress_pattern`: Structured stress annotation including:

  * `binary`: Sequence of 0/1 labels marking stressed words.
  * `indices`: Stressed word positions in the transcription.
  * `words`: The actual stressed words.
* `audio_lm_prompt`: The prompt used for SSR.

---

## Evaluate YOUR model

This dataset is designed for evaluating models following the protocol and scripts in our [StressTest repository](https://github.com/slp-rl/StressTest).

To evaluate a model, refer to the instructions in the repository. For example:

```bash
python -m stresstest.evaluation.main \
    --task ssr \
    --model_to_evaluate stresslm
```

Replace `ssr` with `ssd` for stress detection, and use your model’s name with `--model_to_evaluate`.

---

## How to use

This dataset is formatted for with the HuggingFace Datasets library:

```python
from datasets import load_dataset

dataset = load_dataset("slprl/StressTest")
```

---

## 📖 Citation

If you use this dataset in your work, please cite:

```bibtex
@misc{yosha2025stresstest,
      title={StressTest: Can YOUR Speech LM Handle the Stress?},
      author={Iddo Yosha and Gallil Maimon and Yossi Adi},
      year={2025},
      eprint={2505.22765},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.22765},
}
```