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The aim of the paper is to detect the emotions which are elicited by the speaker while speaking. Emotion Detection has become a essential task these days. The speech which is in fear, anger, joy have higher and wider range in pitch whereas have low range in pitch. Detection of speech is useful in assisting human machine interactions. Here we are using different classification algorithms to recognize the emotions , Support Vector Machine , Multi layer perception, and the audio feature MFCC, MEL, chroma, Tonnetz were used. These models have been trained to recognize these emotions (Calm, neutral, surprise, happy, sad, angry, fearful, disgust). We got an accuracy of 86.5% and testing it with the input audio we get the same.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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