Self-speech evaluation with speech recognition and gesture analysis

Abstract

Speaking helps people to improve their communication, public speaking and leadership skills. There are two main techniques that help a speaker to deliver a meaningful speech. The techniques are voice transition which expresses a verbal message and gestures that convey the message to an audience. A famous organization to help and improvise speech is Toastmasters. Their systems of evaluation are such as, Tracking Filler words, Usage of Redundant words and Phrases, Checking Grammar and Pronunciation, Usage of Body Movements and Gestures, Tracking Vocal Variations and Time Management. If an ordinary person wants to self-evaluate his or her speech, that person has to be a member of a Toastmasters Club or any other speech improvising organization. By using our application, it is possible for a person to evaluate his or her own speech without depending on an organization. All the above-mentioned criteria in manual evaluation processes are included in this application. Since nowadays mobile applications are frequent in use, our system is proposed in Android Platform. Several techniques and methods are used to interconnect with Android such as OpenCV, Microsoft Cognitive Services and MATLAB in order to achieve the objectives of the application. Acoustic Model, Support Vector Model (SVM), Hidden Markov Model (HMM) are some models used to build the application more efficient by giving approximately accurate results.