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---
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: interpretation_id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- 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: 29451897.32142857
num_examples: 218
download_size: 22754357
dataset_size: 29451897.32142857
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 16kHz 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},
}
``` |