Detecting the speaker based on his voice. In this project, we mainly deal with Text-Dependent Speaker recognition system i.e., speaker has to speak a specific word to detect his voice. This algorithim is Generics licensed to the original author
- We record an audio sample of each speaker and save them in a folder called 'Train' with their Speaker ID
- During testing phase, we record an audio sample of any speaker and compute MFCC(Mel Freq Cepstral Co-efficients) using mfcc alogorithm and also save it in a folder called 'Test'.
- We then compute MFFC of all samples saved in 'Train' folder and find Euclidian distance between MFCC of test file and MFCC's of train files.
- The least distance between the test model and train model gives the speaker ID.
- To train any speaker model, first go to the directory where this files are located and type the command "name = train('Train/name')". name - speaker ID
- To find the speaker who is speaking, type the command "test('Test/name')". name - Speaker ID
- Output will give all the Euclidian Distances and Final Speaker ID.
- NOTE : Try to record the audio samples in same environment and in same length.