Types Of Speech Databases - 1068 Words

IV. Speech Databases Once the features used for emotion detection are selected, the feature vector for a number of training data samples should be obtained. Consequently, the next important phase of building the SER system is to select the database. Prior to selecting the database, it is vital to understand the different kinds of databases available with speech percepts [4]. Datasets for speech signals that can be used for emotion detection should be tagged with a text label that denotes the category of emotion expressed in the speech. Based on the environment used for data collection, the databases can belong to one of the following categories. 1. A simulated dataset in one in which actors who are trained artists record speech percepts in†¦show more content†¦The volunteers belonged to different genders and cultures and spoke different languages. The emotions recorded in this dataset belong to six categories, namely: Anger, disgust, fear, joy, sadness and surprise. V. Speech Emotion Detection Algorithms The main function of the emotion detection system is to use all the collected data and its features to identify the emotion expressed in it. To perform this a classifier algorithm can be used to create a classification model. There are several options of classification algorithms that can be used for this purpose. Some of the top choices of algorithm based on research and existing systems include Bayes classifier, Support Vector Machines (SVM), Gaussian Mixture Model (GMM), K-nearest neighbors (KNN), Hidden Markov Models (HMM) and Artificial Neural Networks (ANN). Bayes classifier [11] is one of the oldest classification algorithm that works based on the Bayes Theorem. Bayes theorem works based on prior probability values and assumes independence between the features used for analysis. The bayes classification model works efficiently on very large datasets. It is simple and easy to build. Bayes classifier used in emotion detection for speech gives an average accuracy of 67%. The nearest neighbor algorithm is a lazy learning algorithm that analyses many training data samples and relates every test data sample to the closest matching train data sample to produce an output [12]. In this algorithm aShow MoreRelatedThe Evolution Of Database Management System1099 Words   |  5 PagesThe Evolution of DBMS A database management system, also known as DBMS, is a type of software that is used in order to create and manage a multitude of databases. Data is the power that runs most modern businesses. This specific program provides a technique for people to use a â€Å"systematic† way to create, retrieve, update, and manage many diverse types of data. DBMS is used to manage three important things, which is data, database engine, and database schema. 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