02-11-2012, 11:43 AM
Attendance through Voice Recognition
Attendance through.doc (Size: 412.5 KB / Downloads: 40)
Introduction
The project “Attendance through Voice Recognition” is a tool that can help an organization or academic institute to have attendance of their employee or students and also the faculty members.It also record the time and date at which the member is present.
This project allows a organization or academic institute to overcome the problem of proxy to a great extend.
Many organization is facing the problem of proxy. Employee may mark their attendance by some other guy and the organization may not detect it because there is no such process of verification and it is difficult to recognize the face or voice of every person.
The same situation is their in academic institute also.
The faculty member may mark their attendance though they are late or absent from the institute by some other colleagues which is a common scenario in a government institute.
The faculty members can also get help from this software by detecting proxy of students also.
Initial Problem
Speech is a natural mode of communication for people. We learn all the relevant skills during early childhood, without instruction, and we continue to rely on speech communication throughout our lives. It comes so naturally to us that we don't realize how complex a phenomenon speech is. The human vocal tract and articulators are biological organs with nonlinear properties, whose operation is not just under conscious control but also affected by factors ranging from gender to upbringing to emotional state. As a result, vocalizations can vary widely in terms of their accent, pronunciation, articulation, roughness, nasality, pitch, volume, and speed; moreover, during transmission, our irregular speech patterns can be further distorted by background noise and echoes, as well as electrical characteristics (if telephones or other electronic equipment are used). All these sources of variability make speech recognition, even more than speech generation, a very complex problem.
How to Compare Recordings
Frequency Domain
Given the difficulties mentioned in the above paragraph, one thing becomes very evident. That is, any attempt to analyze sounds in time domain will be extremely impractical. Instead, this led us to analyze the frequency spectra of a voice which remains predominately unchanged as speech is slightly varied. We then effectively utilized the Discrete Fourier Transform to convert all recording into frequency domain before any comparisons were made. Working in frequency domain eliminates the necessity to exactly align audio tracks in order to make a comparison.
Algorithm Instructions
The project contain a folder named 'Matlab Files' contains 10 audio recordings of the person whose voice is to be recognized.
Every person should record his 10 voice saying his name.
Also, that folder contains two m-files. These two files are project.m and voicerec.m.
Project.m is the voice recognition program that accomplishes the goals of the class project. The script file project.m can be ran in the command window in Matlab. Please ensure that the directory in Matlab is set to the directory that contains project.m and the audio recordings.
Once project.m is ran in Matlab, it will then ask you to "Enter the name that must be recognized".Then type in the name that has to be recognized but the name that is typed must have its recorded voice in the audio folder.
After that, the program will let you know that you have 2 seconds to record yourself saying “The name”. After recording, Matlab will play this recording and you will then have the option to record again or proceed with your recording. After proceeding, Matlab will generate a plot showing how the normalized frequency spectra in your voice (Top window) compares to the average normal vector of Typed name Voice(Bottom window)