Commercial
Speech Emotion Recognition Dataset
A voice dataset featuring the same English text spoken with four different emotional tones
Request a demo- Emotion Recognition The ability to identify and classify emotions based on vocal cues
- Speech Analysis The study of speech patterns and characteristics
- Audio The use of machine learning techniques to process audio data
- NLP The ability of a system to understand, analyze and interpret human's languages
- 30,000+
- audio
- 4
- emotions
CASE DESCRIPTION
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The texts are delivered in English and embody four distinct emotional states: euphoria, joy, sadness, and surprise.
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Every audio clip reflects the tone, intonation, and subtleties of speech as individuals express their emotions vocally.
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The dataset includes diverse speakers of various ages, genders, and cultural backgrounds, offering a broader representation of emotions.
Application areas of the dataset
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01.
Sentiment Analysis:
Utilize the dataset to train models that analyze and interpret emotional sentiment in spoken language. -
02.
Automatic Emotion Detection:
Develop systems capable of detecting emotions in real-time speech for applications in customer service and mental health. -
03.
Emotional Speech Synthesis:
Create more human-like voice synthesis systems that can convey emotions effectively. -
04.
Voice Assistants:
Dataset to train virtual assistants and improve their response accuracy and natural language processing capabilities.
