Voice/Music acoustic signal processing techniques with explicative GUI.
-
Hidden Markov Model with MFCC as feature vector for simple voice recognition
-
Non-negative Matrix Factorization for Sound Separation
-
Autocorrelation / Subharmonic Summation for pitch detection
-
Real-time or file input
-
Display multiple charts as of entire period or specified frame length.
-
Display calculation and recognition results: loudness, fundamental frequency, Japanese vowel prediction,...
Waveform of entire period with marker indicating current position.
Waveform of current frame.
Spectrogram with display of voiced / unvoiced period differentiated using zero-crossing rate and fundamental frequency.
Autocorrelation and fundamental frequency position (second peak)
Display filter spectrum (default: lifter order 13) in comparison with original spectrum.
Using saved training result to determine a / i / u / e / o period.