Python(Keras lib for Neural Networks) + OpenCV 3.0
The main goal of this project is to recognize (fingerprint) short audio samples, such as short speech command, whistle, or any other sound from nature and map them to specific action.
Using sound samples for reaching your goal: - Sound recognition of songs (music) , sounds from nature, human voice - Using human voice for commanding smarthpone, smart vehicle during the ride - Can be of great use to people with major disability.
- So far, software is trained to recognize whistle melodies and short audio samples.
It can be easly upgraded to recognize specific types of sound.
- Sound recognition in real-time (not from audio samples, live recording from mic)
- New data-sets and new training
- Main frame:
- Application output:
- Test analyze - FFT:
- Test analyze - Waveform:
- Test analyze - Spectrogram:
- Test analyze - Spectrogram - Black and White (ready as Neural Network input):
- MIT
Great spectrogram article <br/ > University Of Novi Sad, Faculty Of Techical Scieces, AI-lab