Portuguese-audio-dataset

# Portuguese Voice Emotion Dataset
*This dataset contains high-quality (“A-grade”) data. It has been carefully curated, cleaned, and verified to ensure accuracy, completeness, and consistency, making it suitable for high-stakes or production-grade model training.

## Dataset Summary

This dataset comprises high-quality Portuguese speech recordings designed for training and evaluating Speech Emotion Recognition (SER) models. The dataset contains voice samples expressing four distinct emotions: **Angry**, **Happy**, **Sad**, and **Surprised**. Each recording is categorized by speaker demographics (age, gender: Male/Female), providing a comprehensive resource for emotion classification research in Portuguese speech.

## Contact

For queries or collaborations related to this dataset, contact:
- [e-mail]
- [e-mail]

## Supported Tasks

- **Task Categories**: Speech Emotion Recognition (SER)
- **Supported Tasks**:
- Emotion classification from speech
- Audio signal processing for affective computing
- Speaker demographic analysis
- Cross-cultural emotion recognition research
- Voice synthesis with emotional expression (secondary use)

## Languages

- **Primary Language**: Portuguese

## Dataset Creation

### Curation Rationale

This dataset was created to advance Portuguese speech emotion recognition research by providing labeled emotional speech samples across different demographic groups. The inclusion of age and gender metadata enables research into how emotional expression varies across demographics in Portuguese speech patterns.

### Source Data

- **Contributors**: Portuguese native speakers across different age groups and genders
- **Recording Guidelines**: Speakers were asked to express specific emotions naturally in Portuguese, ensuring authentic emotional expression while maintaining audio quality standards.

### Annotations

- **Annotation Process**: Each audio file is manually labeled with emotion, age group, and gender information
- **Annotators**: Native Portuguese speakers familiar with emotional expression patterns
- **Quality Control**: Multiple validation steps to ensure emotion labels match audio content

### Other Known Limitations

- **Size**: Relatively small dataset may limit model generalization
- **Emotion Categories**: Limited to four basic emotions; complex or mixed emotions not represented
- **Audio Quality**: Variations in recording conditions may affect model performance
- **Regional Dialects**: May not represent all Portuguese regional speech patterns

## Intended Uses

### ✅ Direct Use

- Training and benchmarking Speech Emotion Recognition models for Portuguese
- Research in cross-cultural emotion recognition
- Development of Portuguese-language affective computing applications
- Academic research in computational linguistics and psychology

### ❌ Out-of-Scope Use

- Real-time production systems without additional validation
- Clinical or diagnostic applications for mental health
- Commercial use without proper attribution
- Surveillance or privacy-invasive applications

## License

CC BY 4.0

# 葡萄牙语语音情感数据集
*本数据集采用高质量（A级）数据，经过精心筛选、清理与验证，确保数据的准确性、完整性与一致性，适用于高要求场景或生产级模型训练。*

## 数据集概述
本数据集包含高质量葡萄牙语语音录音，专为语音情感识别（Speech Emotion Recognition, SER）模型的训练与评估设计。数据集包含表达四种不同情感的语音样本：**愤怒、开心、悲伤与惊讶**。每条录音均标注了说话者的人口统计信息（年龄、性别：男/女），为葡萄牙语语音情感分类研究提供了全面的资源。

## 联系方式
如有关于本数据集的咨询或合作需求，请联系：
- [e-mail]
- [e-mail]

## 支持任务
- **任务类别**：语音情感识别（Speech Emotion Recognition, SER）
- **支持任务**：
- 语音情感分类
- 面向情感计算的音频信号处理
- 说话者人口统计分析
- 跨文化情感识别研究
- 带情感表达的语音合成（次要用途）

## 语言类型
- **主要语言**：葡萄牙语

## 数据集构建
### 筛选依据
本数据集旨在推动葡萄牙语语音情感识别研究，通过提供覆盖不同人口统计群体的标注情感语音样本。纳入年龄与性别元数据，可用于研究葡萄牙语语音模式中，情感表达如何随人口统计特征变化。

### 源数据
- **贡献者**：来自不同年龄组与性别的葡萄牙语母语者
- **录音规范**：要求说话者以自然方式用葡萄牙语表达特定情感，在保证音频质量标准的同时，确保情感表达的真实性。

### 标注流程
- **标注过程**：每条音频文件均由人工标注情感类别、年龄组与性别信息
- **标注人员**：熟悉情感表达模式的葡萄牙语母语者
- **质量控制**：采用多轮验证步骤，确保情感标签与音频内容匹配

### 其他已知局限性
- **数据规模**：数据集规模相对较小，可能限制模型的泛化能力
- **情感类别**：仅涵盖四种基础情感，未包含复杂或混合情感
- **音频质量**：录音环境存在差异，可能影响模型性能
- **区域方言**：未能覆盖所有葡萄牙语区域的语音模式

## 预期用途
### ✅ 直接用途
- 葡萄牙语语音情感识别模型的训练与基准测试
- 跨文化情感识别研究
- 葡萄牙语情感计算应用的开发
- 计算语言学与心理学领域的学术研究

### ❌ 超出范围的用途
- 未经额外验证的实时生产系统
- 用于心理健康的临床或诊断应用
- 未经适当署名的商业使用
- 监视或侵犯隐私的应用

## 许可证
CC BY 4.0