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ABSTRACT
The speech signal is one of the most natural and fastest methods of
communication between humans. Many systems have been developed
by various researchers to identify the emotions from the speech signal.
In differentiating between various emotions particularly speech features
are more useful and if not clear is the reason that makes emotion
recognition from speaker‘s speech very difficult. There are a number of
the dataset available for speech emotions, it’s modelling, and types that
helps in knowing the type of speech. After feature extraction, another
important part is the classification of speech emotions so the paper has
compared and reviewed the different classifiers that are used to
differentiate emotions such as sadness, neutral, happiness, surprise,
anger, etc. The research also shows the improvement in emotion
recognition system by making automatic emotion recognition system
adding a deep neural network. The analysis has also been performed
using different ML techniques for Speech emotions recognition accuracy
in different languages.
