slprl/Stress-17K-raw

Stress-17K是一个合成数据集，旨在支持StresSLM模型的指令微调，用于处理句子重音检测（SSD）和句子重音推理（SSR）任务。数据集通过向原始重音话语样本中添加任务特定的提示来构建，使模型能够更有效地学习SSD和SSR。数据集包含两个子集：train_full包含全部生成的样本，而train_fine是通过WhiStress模型预测筛选出的验证子集。

Stress-17K is a synthetic dataset designed to support instruction tuning for the StresSLM model tackling Sentence Stress Detection (SSD) and Sentence Stress Reasoning (SSR) tasks. The dataset is constructed by augmenting a raw dataset of stressed speech samples with task-specific prompts, enabling models to learn SSD and SSR more effectively. The dataset includes two subsets: train_full contains the full set of generated samples, while train_fine is a verified subset derived by filtering train_full using predictions from the WhiStress model.