Talking Diary: A Novel Approach for Automatic Audio Note Categorization and Event Scheduling for Android Application

Smartphone usage is very common nowadays. People tried to regulate their routine tasks using different mobile applications. In this research, a novel approach for note classification and scheduling is proposed to facilitate mobile users in automatically organizing their daily routine tasks with a single audio note. The proposed model has been implemented in an android application named-Talking Diary. Talking Diary is an android application comprised of three modules namely auto audio note classification, auto audio note scheduling, and working hour's calculator. The proposed model of classifier computed similarity score by extracting N-gram weights from Concept Net to perform classification. The scheduler generates events and alarm on receiving the audio note. Working hours are calculated on the basis of using GPS location. Testing of Talking Diary android application is performed by collecting 500 sample notes from the random population of participants. Accuracy, Recall, and Precision is calculated for the correctness of classifier. Test cases were developed to ensure the performance of the scheduler and work hour calculator.