FourcommonlyusedaudiofeaturesVolume四种常用的音频特征量.ppt

1、Basic Features of Audio Signals(音訊的基本特徵),Jyh-Shing Roger Jang (張智星) .tw/jang MIR Lab, CS Dept, Tsing Hua Univ. Hsinchu, Taiwan,Audio Features,Four commonly used audio features Volume Pitch Zero crossing rate Timber Our goal These features can be perceived subjectively. But we ne

2、ed to compute them quantitatively for further processing and recognition.,Audio Features in Time Domain,Audio features presented in the time domain,Intensity,Fundamental period,Timbre: Waveform within an FP,Audio Features in Frequency Domain,Volume: Magnitude of spectrum Pitch: Distance between harm

3、onics Timber: Smoothed spectrum,Second formant F2,First formant F1,Pitch freq,Intensity,Demo: Real-time Spectrogram,Try “dspstfft_audio” under MATLAB:,Spectrogram:,Spectrum:,Steps for Audio Feature Extraction,Frame blocking Frame duration of 20 ms or so Feature extraction Volume, zero-crossing rate,

4、 pitch, MFCC, etc Endpoint detection Usually based on volume duration=3; f=440; t=(1:fs*duration)/fs; y=0.8*sin(2*pi*f*t); plot(t,y); axis(0.6, 0.65, -1 1); sound(y, fs);,Zero Crossing Rate,Zero crossing rate (ZCR) The number of zero crossing in a frame. Characteristics： Noise and unvoiced sound hav

5、e high ZCR. ZCR is commonly used in endpoint detection, especially in detection the start and end of unvoiced sounds. To distinguish noise/silence from unvoiced sound, usually we add a bias before computing ZCR.,ZCR Computations,Two types of ZCR definition If a sample with zero value is considered a case of ZCR, then the value of ZCR is higher. Otherwise its lower. It affects the ZCR, especially when the sample rate is low. Other consideration Zero-justification is required. ZCR with shift can be used to distinguish between unvoiced sounds and sile