Seamless speaker recognition

Abstract: In a technologically advanced society, the average person manages dozens of accounts for e-mail, social networks, e-banking, and other electronic services. As the number of these accounts increases, the need for automatic user identification becomes more essential. Biometrics have long been used to identify people and are the most common (if not the only) method to achieve this task. Over the past few years, smartphones have become frequently used gadgets.  These devices have built-in microphones and are commonly used by a single user or a small set of users, such as a couple or a family. This thesis uses a smartphone’s microphone to capture user’s speech and identify him/her. Existing speaker recognition systems typically prompt the user to provide long voice samples in order to provide accurate results. This results in a poor user experience and discourages users who do not have the patience to go through such a process.  The main idea behind the speaker recognition approach presented in this thesis is to provide a seamless user experience where the recording of the user’s voice takes place in the background. An Android application is developed which silently collects voices samples and performs speaker recognition without requiring extensive user interaction.  Two variants of the proposed tool have been developed and are described in depth in this thesis. The open source framework Recognito is used to perform the speaker recognition task. The analysis of Recognito showed that it is not capable of achieving high accuracy especially when the voice samples contain background noise. Finally, the comparison between the two architectures showed that they do not differ significantly in terms of performance.