Datasets:
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license: cc-by-nc-sa-4.0
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---
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license: cc-by-nc-sa-4.0
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---
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# S2S-Bench Dataset
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This repository hosts the **S2S-Bench** dataset. It covers four practical domains with 21 tasks, includes 154 instructions of varying difficulty levels, and features a mix of samples from TTS synthesis, human recordings, and existing audio datasets.
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## Introduction
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### GitHub Repository
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For more information and access to the dataset, please visit the GitHub repository:
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[S2S-Bench on GitHub](https://github.com/FreedomIntelligence/S2S-Bench)
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### Related Publication
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For detailed insights into the dataset’s construction, methodology, and applications, please refer to the accompanying academic publication: `[Insert publication link here]`
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## Data Description
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The dataset includes labeled audio files, textual emotion annotations, language translations, and task-specific metadata, supporting fine-grained analysis and application in machine learning. Each entry follows this format:
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```json
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{
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"id": "emotion_audio_0",
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"input_path": "./emotion/audio_0.wav",
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"text": "[emotion: happy]Kids are talking by the door",
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"task": "Emotion recognition and expression",
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"task_description": "Can the model recognize emotions and provide appropriate responses based on different emotions?",
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"text_cn": "孩子们在门旁说话",
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"language": "English",
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"category": "Social Companionship",
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"level": "L3"
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}
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```
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1. id: Unique identifier for each sample
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2. input_path: Path to the audio file
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3. text: English text with emotion annotation
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4. task: Primary task associated with the data
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5. task_description: Task description for model interpretability
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6. text_cn: Chinese translation of the English text
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7. language: Language of the input
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8. category: Interaction context category
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9. level: Difficulty or complexity level of the sample
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"Some data also includes a `noise` attribute, indicating that noise has been added to the current sample and specifying the type of noise."
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## BIb
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```
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```
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