Sound Operated Device Control System

Arjav Bavarva is assistant professor in ECE department, School of Engineering, RK University, Gujarat. He is LabVIEW associate developer certified and coordinator of NI LabVIEW Academy, RK University. Rahul Vyas, Parth Gangadia and Faizal Panavadhu are pursuing B. Tech (ECE) from School of Engineering, RK University, Gujarat


In movies like Ironman and Players, it is shown that appliances are operated by human speech or sound. Similar concept of a sound operated device control system implemented in this project. The system responds to pre-stored sound and performs particular functions. That is, command signals are first stored in the database and when you run the project, a real-time sound or speech signal is compared with the signals stored in the database. If signals match, an appliance/load is turned on/off. For instance, sound command ‘Switch on the fan’ is used to operate the fan.

This project has vital applications especially for the differently abled and can also be used to provide security and authentication.

Sound operated device control system block diagram

Fig. 1: Block diagram of the project with connections between different modules

The project can be developed by various methods using different algorithms like biometrics, fuzzy logic, neural networks and hidden Markov. The easiest and most efficient method is cross-correlation algorithm implemented by LabVIEW software. Fig. 1 shows the block diagram of the project with connections between different modules. Various processes like speech acquisition, speech filtering, speech comparison and decision making are easy to program in LabVIEW because of its user-friendly graphical programming environment.

Fig. 2: Wav file creation VI
Fig. 3: Comparison of wav file

A predefined command is stored in the system. With the help of a microphone, real-time sound signal is acquired by LabVIEW functional block. This acquired sound is not suitable for cross-correlation or comparison because of the noise within the real-time speech.

Fig. 4: Front panel of the comparison of wav file VI

So it is advisable to filter the acquired signal using low-pass Butterworth filter to remove unwanted frequencies or noises. Low-pass Butterworth filter gives flat frequency response.

Fig. 5: Serial communication VI

Output of the filter is given to the cross-correlation block to compare this signal with pre-stored command. We have used AT89S51 as controller.

The project includes the following programs: Wav file Creation Sub, Cross, Serial for front end LabVIEW program and Voice.c for the AT89S51 microcontroller.



Please enter your comment!
Please enter your name here