A smart audio on demand application on android systems

Abstract

This paper describes a study of the realization of intelligent Audio on Demand (AOD) processing in the embedded system environment. This study describes the development of innovative Android software that will enhance user experience of the increasingly popular number of smart mobile devices now available on the market. The application we developed can accumulate records of the songs that are played and automatically analyze the favorite song types of a user. The application can also select sound control playback functions to make operation more convenient. A large number of different types of music genre were collected to create a sound database and build an intelligent AOD processing mechanism. Formant analysis was used to extract voice features and the K-means clustering method and acoustic modeling technology of the Gaussian mixture model (GMM) were used to study and develop the application mechanism. The processes we developed run smoothly in the embedded Android platform.