StressTest
Collection
Model and Data from the paper - StressTest: Can YOUR Speech LM Handle the Stress?
β’
3 items
β’
Updated
β’
1
StresSLM is an audio-text-to-text model fine-tuned with LoRA adapters on top of the Qwen/Qwen2-Audio-7B-Instruct
base model. It is designed to tackle Sentence Stress Detection (SSD) and Sentence Stress Reasoning (SSR) tasks on the StressTest benchmark.
StresSLM predicts stress patterns and reasoning based on spoken audio.
For more information, see our paper and code:
π StressTest Paper | π» Code | π€ StressTest Dataset
This model can be loaded using the HuggingFace Transformers library:
from transformers import AutoProcessor, Qwen2AudioForConditionalGeneration
from peft import PeftModel, PeftConfig
# Load processor
processor = AutoProcessor.from_pretrained("Qwen/Qwen2-Audio-7B-Instruct")
# Load LoRA config and base model
peft_config = PeftConfig.from_pretrained("slprl/StresSLM")
base_model = Qwen2AudioForConditionalGeneration.from_pretrained(peft_config.base_model_name_or_path)
# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "slprl/StresSLM")
For evaluation scripts and benchmarks, refer to the StressTest GitHub repository.
If you use this model, please cite:
@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},
}
Base model
Qwen/Qwen2-Audio-7B-Instruct