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README.md

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-license: cc-by-nc-nd-4.0
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+---
+license: cc-by-nc-nd-4.0
+task_categories:
+- automatic-speech-recognition
+- audio-classification
+tags:
+- audio
+- speech
+- recognition
+- emotion
+- NLP
+size_categories:
+- 10K<n<100K
+---
+# Speech Emotion Recognition
+Dataset comprises **30,000+** audio recordings featuring **4** distinct emotions: euphoria, joy, sadness, and surprise. This extensive collection is designed for research in **emotion recognition**, focusing on the nuances of **emotional speech** and the subtleties of **speech signals** as individuals vocally express their feelings.
+
+By utilizing this dataset, researchers and developers can enhance their understanding of **sentiment analysis** and improve **automatic speech processing** techniques. - **[Get the data](https://unidata.pro/datasets/speech-emotion-recognition/?utm_source=huggingface&utm_medium=cpc&utm_campaign=speech-emotion-recognition)**
+
+Each audio clip reflects the tone, intonation, and emotional expressions of diverse speakers, including various ages, genders, and cultural backgrounds, providing a comprehensive representation of human emotions. The dataset is particularly valuable for developing and testing recognition systems and classification models aimed at detecting emotions in spoken language.
+
+# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/speech-emotion-recognition/?utm_source=huggingface&utm_medium=cpc&utm_campaign=speech-emotion-recognition) to discuss your requirements and pricing options.
+
+Researchers can leverage this dataset to explore deep learning techniques and develop classification methods that improve the accuracy of emotion detection in real-world applications. The dataset serves as a robust foundation for advancing affective computing and enhancing speech synthesis technologies.
+# 🌐 [UniData](https://unidata.pro/datasets/speech-emotion-recognition/?utm_source=huggingface&utm_medium=cpc&utm_campaign=speech-emotion-recognition) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects