Abstract
In this artificial intelligence time, speaker recognition is the most useful biometric recognition technique. Security is a big issue that needs careful attention because of every activities have been becoming automated and internet based. For security purpose, unique features of authorized user are highly needed. Voice is one of the wonderful unique biometric features. So, developing speaker recognition based on scientific research is the most concerned issue. Nowadays, criminal activities are increasing day to day in different clever way. So, every country should have strengthen forensic investigation using such technologies. The study was done by inspiration of contextualizing this concept for our country. In this study, text-independent Amharic language speaker recognition model was developed using Mel-Frequency Cepstral Coefficients to extract features from preprocessed speech signals and Artificial Neural Network to model the feature vector obtained from the Mel-Frequency Cepstral Coefficients and to classify objects while testing. The researcher used 20 sampled speeches of 10 each speaker (total of 200 speech samples) for training and testing separately. By setting the number of hidden neurons to 15, 20, and 25, three different models have been developed and evaluated for accuracy. The fourth-generation high-level programming language and interactive environment MATLAB is used to conduct the overall study implementations. At the end, very promising findings have been obtained. The study achieved better performance than other related researches which used Vector Quantization and Gaussian Mixture Model modelling techniques. Implementable result could obtain for the future by increasing number of speakers and speech samples and including the four Amharic accents.
Highlights
Speech is a medium for human to express their thoughts during communication
The goal of this study is exploring the possibility of a state of the art modeling techniques for building Amharic language speaker recognition
Amr Rashed, 2014, this paper proposed a fast algorithm for speaker recognition
Summary
Speech is a medium for human to express their thoughts during communication. A speech signal is a complex signal which is packed with several knowledge resources such as acoustic, articulatory, semantics, linguistic and many more. Speaker recognition which is the concern of this study is the process of automatically recognizing who is speaking by using the speaker-specific information included in speech waves to verify identities being claimed by people accessing systems; that is, it enables access control of various services by voice [2]. This study is dealt with text-independent speaker identification in a case of Amharic language speech. For developing countries like Ethiopia, it is a must, to follow the outfit of those techno-rich countries in relation to such technological advancements to do not lose the opportunities provided by technologies Based on this fact, speech engineers and language experts invarious countries are making noticeable efforts to develop recognition that works for their own language. The goal of this study is exploring the possibility of a state of the art modeling techniques for building Amharic language speaker recognition
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More From: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
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