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Speech Recognition using python

Speech Recognition

Price : 5000

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Course Duration
Approx 10

Course Price
₹ 5000

Course Level
Moderate

Course Content

 

Recognizing emotions is automatically and subconsciously performed by humans. It is a vital process for human-to human communication, and thus, to achieve better human machine interaction, emotions need to be considered. Emotional speech recognition importance is growing in several domains. Researchers have raised the impact of emotion in multidisciplinary applications. Predicting human emotions is catching the attention of many research areas, which demand accurate predictions in uncontrolled scenarios. Psychologists have widely studied the influence of emotional factors, on decision-making. As example, pilots’ decision in a flight context may jeopardize several humans’ life. The importance of recognizing emotion for needs of the real world use is becoming unavoidable. In real world applications, speech signals are often corrupted by acoustic background noise. In these applications, speech enhancement is a necessary module for the emotion recognition system. Despite recent advances in the field of automatic speech emotion recognition, recognize emotions from vocal channel in noisy environment remains an open research problem. We proposed a system that will do Speech detection and Continuous recognition of emotions from speech.

 

PROPOSED SYSTEM

 

We proposed a new model for continuous emotion recognition from speech. Our model, which was trained end-to-end, is comprised of a Convolutional Neural Network (CNN), which extracts features from the raw signal and does the speech detection and continuous emotion recognition from speech.

 

Hardware Requirements

Ø System: Pentium IV 2.4 GHz.

Ø Hard Disk: 500 GB.

Ø Ram: 4 GB.

Ø Any desktop / Laptop system with above configuration or higher level.

 

 

Software Requirements

Ø Operating system : Windows XP / 7

Ø Coding Language :Python

Ø Interpreter  :Python 3.6

Ø IDE   : Jupyter notebook

 

 

Recognizing emotions is automatically and subconsciously performed by humans. It is a vital process for human-to human communication, and thus, to achieve better human machine interaction, emotions need to be considered. The Automated Speech Emotion Recognition is a tough process because of the gap among acoustic characteristics and human emotions, which depends strongly on the discriminative acoustic characteristics extracted for a provided recognition task. Different persons have different emotions and altogether a different way to express it. Speech emotion do have different energies, pitch variations are emphasized if considering different subjects. Therefore, the speech emotion detection is a demanding task in computing vision. Here, the speech emotion recognition is based on the Convolutional Neural Network (CNN) algorithm which uses different modules for the emotion recognition and the classifiers are used to differentiate emotions such as happiness, surprise, anger, neutral state, sadness etc. Emotional speech recognition importance is growing in several domains. So a solution to this we proposed a system that will do Speech detection and Continuous recognition of emotions from speech.

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