卷積神經網路之語音密碼系統

Abstract

現今的社會基於安全上的需要以及便利性，有需多不同種類的生物辨識系統因應而生，所謂的生物辨識技術就是以每一個生物獨有的生物特徵當作辨識的依據像是指紋辨識、虹膜辨識等等，其中說話人辨認也是生物辨識的其中一種，如果有一天，解鎖系統能透過說話人的聲音以及說出的密碼來辨別是不是手機的擁有者，勢必能讓生活更方便。 由於AlphaGo與李世石的圍棋對決使得深度學習突然成為了顯學，如何將類神經網路應用於各個領域的問題也成為了大家爭相研究的題目，其中卷積神經網路的發展也是類神經網路發展的其中一個重要的領域，本論文提出了一個基於卷積神經網路設計的語音密碼系統，利用說話人的語音訊號生成之灰階影像，將之輸入至卷積神經網路並產出分類結果，並搭配辨識語者說出的密碼，以達成辨識語音密碼的功能。

There are many different types of biometric systems that are developed because of the need for security and convenience. The biometric technology is based on the unique biological characteristics of each organism such as fingerprint recognition, iris recognition, etc. The voice recognition is also one of the biometric characteristic. One day, people may unlock their cellphone by just talking to their cellphone which make life more convenient. Deep Learning has become one of the most popular research topic becase of ALPHAGO. Everyone started to study how to apply deep learning to a variety of problems and the convolutional neural networks is also an important area in the development of neural networks. This research proposes a vocal password recognition system based on convolutional neural network. Using the grayscale image generated by the speaker’s voice signals as an input to the convolutional neural network and use it to produce the classfication result to build the vocal password recognition system.