HEARING SOFTWARE

Humans are able to comprehend information from multiple domains for ex.: speech, text and visual. With advancement of deep learning technology there has been significant improvement of speech recognition. Recognizing emotion from speech is important aspect and with deep learning technology emotion recognition has improved in accuracy and latency. There are still many challenges to improve accuracy. We explore different neural networks to improve accuracy of emotion recognition. With different architectures explored, we find multi-model architecture which processes audio spectrograms and corresponding video frames giving emotion prediction.