- Through all the available senses humans can actually sense the emotional state of their communication partner.
- The emotional detection is natural for humans but it is very difficult task for computers; although they can easily understand content based information, accessing the depth behind content is difficult and that’s what speech emotion recognition (SER) sets out to do.
- It is a system through which various audio speech files are classified into different emotions such as happy, sad, anger and neutral by computer.
- SER can be used in areas such as the medical field or customer call centers. With this project I hope to look into applying this model into an app that individuals with ASD can use when speaking to others to help guide conversation and create/maintain healthy relationships with others who have deficits in understanding others emotions.
The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) Dataset from Kaggle contains 1440 audio files from 24 Actors vocalizing two lexically-matched statements. Emotions include angry, happy, sad, fearful, calm, neutral, disgust, and surprised.
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