Salient Cross-Lingual Acoustic and Prosodic Features for English and German Emotion Recognition

2016 ◽  
pp. 159-169
Author(s):  
Maxim Sidorov ◽  
Christina Brester ◽  
Stefan Ultes ◽  
Alexander Schmitt
Keyword(s):  
Emotion Recognition ◽  
Prosodic Features ◽  
Cross Lingual

Emotion recognition from speech using wavelet packet transform and prosodic features

2018 ◽  
Vol 35 (2) ◽  
pp. 1541-1553 ◽  
Author(s):  
Manish Gupta ◽  
Shambhu Shankar Bharti ◽  
Suneeta Agarwal
Keyword(s):  
Emotion Recognition ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Prosodic Features

Emotion Analysis from Human Voice Using Various Prosodic Features and Text Analysis

2020 ◽  
Vol 17 (9) ◽  
pp. 4244-4247
Author(s):  
Vybhav Jain ◽  
S. B. Rajeshwari ◽  
Jagadish S. Kallimani
Keyword(s):  
Emotion Recognition ◽  
Sentiment Analysis ◽  
Text Analysis ◽  
Good Accuracy ◽  
Age Groups ◽  
Speech Emotion Recognition ◽  
Prosodic Features ◽  
Voice Analysis ◽  
Emotion Analysis ◽  
Human Voice

Emotion Analysis is a dynamic field of research with the aim to provide a method to recognize the emotions of a person only from their voice. It is more famously recognized as the Speech Emotion Recognition (SER) problem. This problem has been studied upon from more than a decade with results coming from either Voice Analysis or Text Analysis. Individually, both these methods have shown a good accuracy up till now. But, the use of both of these methods in unison has showed a much more better result than either one of those parts considered individually. When different people of different age groups are talking, it is important to understand their emotions behind what they say as this will in turn help us in reacting better. To try and achieve this, the paper implements a model which performs Emotion Analysis based on both Tone and Text Analysis. The prosodic features of the tone are analyzed and then the speech is converted to text. Once the text has been extracted from the speech, Sentiment Analysis is done on the extracted text to further improve the accuracy of the Emotion Recognition.

Sign in / Sign up

Export Citation Format

Share Document