Neural network utilization for flagged words detection thru distinct audio features

• Main Authors: Mital, Matt Ervin G., Villaruel, Herbert V., Lim, Rommel M., Tobias, Rogelio Ruzcko, Maningo, Jose Martin Z., Bandala, Argel A., Vicerra, Ryan Rhay P., Dadios, Elmer P.
• Format: text
• Published: Animo Repository 2019
• Subjects: Computer sound processing; Auditory scene analysis; Artificial Intelligence and Robotics
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/91
• Institution: De La Salle University

This research paper employed a method of detecting a given flagged word that would possibly trigger a machine and at the same time, being able to separate such sound source in a given real world environment. As part of the experimentation done, the flagged words were recorded by 3 different individuals. To make sure that only the flagged words would be detected by the robot's auditory signal processor, the 3 individuals were also asked to record random words that would be used to test whether the robot's detector responds even in random words being heard. By utilizing the neural networks concepts and processes, detection of flagged words was made possible. After the results has been produced, the researchers arrived to a conclusion that even in the middle of a noisy and reverberant surroundings and situations, the robot can capture the flagged words coming from the crowd by allowing the neural network to perform its function.