Consider a vector of ones with alternating signs. Plot the data.

x = [1 -1 1 -1 1 -1 1 -1 1 -1]; plot(x)

Compute the zero-crossing rate ofx.

r = zerocrossrate(x)

r = 0.9500

Use the third output argument to find the locations where the crossings occur. Plotxand the zero-crossing locations. The function returns an index at the next sample after a crossing, not necessarily the exact crossing location. The first sample is marked as a crossing point because the function considers the initial state ofxto be zero by default.

[~,~,indices] = zerocrossrate(x); plot(x) holdonplot(x(indices),'*') holdoff

Compute the zero-crossing rate ofxusing the comparison method. The rate differs from the value computed using the difference method.

rC = zerocrossrate(x,Method="comparison")

rC = 0.9000

Compute the zero-crossing rate ofxagain using the difference method and specify zero as positive. The rate is equal to the value computed using the comparison method.

rZ = zerocrossrate(x,ZeroPositive=1)

rZ = 0.9000

Now specify the initial state ofxas1. The rate is equal to the previous result.

rI = zerocrossrate(x,InitialState=1)

rI = 0.9000

Load a set of temperature readings in Celsius taken every hour at Logan Airport in Boston for the entire month of January, 2011. Create atimetableand use调整时间to aggregate the data into daily means.

loadbostempt = hours(1:24*31)'; TT = timetable(t,tempC); rTT = retime(TT,'daily','mean');

Count the number of days the temperature crosses the monthly average. Plot the data and include a horizontal line at the monthly average temperature to visualize where the crossings occur.

avg = mean(TT.tempC)

avg = -1.3007

[~,count] = zerocrossrate(rTT,Level=avg)

count = 9

plot(hours(rTT.t/24),rTT.tempC) yline(avg) xlabel('Time elapsed since January 1, 2011 (days)') ylabel('Average daily temperature (\circC)') axistight

Speech can be characterized as being voiced or unvoiced.Voicedspeech, such as vowel sounds, occurs when the vocal cords vibrate. Inunvoicedspeech, such as most consonant sounds, the vocal chords do not vibrate. You can use zero crossings to classify the voiced and unvoiced regions in an audio signal.

Load an audio signal into the MATLAB® workspace. The voice says, "Oak is strong, and also gives shade".

(y, fs) = audioread ("oak.m4a");% To hear, type soundsc(y,fs)

The signal is sampled at 44.1 kHz. Calculate the zero-crossing rate for 10 ms windows using the comparison method.

win = fs*0.01; rate = zerocrossrate(y,WindowLength=win,Method="comparison");

Plotrateto visualize the crossing rate for each segment. Voiced speech is expected to have a low crossing rate, while unvoiced speech is expected to have a high crossing rate.

plot(rate)

Use a threshold of0.1to differentiate between voiced and unvoiced segments. Create asignalMaskobject that has two categories ("Unvoiced" and "Voiced") and plot the regions of interest (ROIs). Compare the regions of voiced and unvoiced speech to the location of each spoken word.

You can use Audio Toolbox™ speech-to-text functionality to extract words from an audio file. Load the labeled signal setlsfromSpeechTranscription.matinto the workspace. The labeled signal set contains the audio signal, ROI limits, and labels for each spoken word. For more information on labeling audio signals, seeLabel Spoken Words in Audio Signals. Display the spoken words on the plot.

h = 0.1; idu = find(rate > h); idu(1:2) = []; vi = [(idu-1) idu]*win; m = sigroi2binmask(vi,length(y)); mask = signalMask([m ~m],Categories=["Unvoiced""Voiced"],SampleRate=fs); plotsigroi(mask,y) loadSpeechTranscriptionln = getLabelNames(ls); v = getLabelValues(ls,1,ln); v.Value = categorical(v.Value,v.Value); RL = v.ROILimits; VL = v.Value; holdontext(mean(RL,2),-0.7*ones(size(VL)),VL,HorizontalAlignment="center",...FontSize=11,FontWeight="bold") holdoff

Load an audio file containing 15 seconds of acoustic guitar music. The sample rate is 44.1 kHz. To play the music, uncomment the last line of code.

Fs = 44100; y = audioread("guitartune.wav");% sound(y,Fs)

Buffer the audio signal into overlapping frames, each with 4096 samples. Use an overlap of 512 samples.

winLength = 4096; overlap = 512; [yB,~] = buffer(y,winLength,overlap,"nodelay");

Obtain the zero-crossing rate for each frame. To account for frame overlap, specify the initial state as the previous value of the first sample in each frame.

init = winLength - overlap; state = 0; zcr = [];fori = 1:size(yB,2) zcr = [zcr;zerocrossrate(yB(:,i),InitialState=state)]; state = yB(init,i);end

Plot the audio signal and overlay the zero-crossing rate for each frame.

figure yyaxisleftx = 0:1/Fs:(numel(y)-1)/Fs; plot(x',y) xlabel("Seconds") ylabel("Amplitude") yyaxisrightxx = (1:size(yB,2))*((winLength-overlap)/Fs); plot(xx',zcr) ylabel("Zero-crossing rate")

计算的零交点率无缓冲的年代ignal. To obtain a result equivalent to the zero-crossing rate of the buffered signal, setWindowLengthto4096andOverlapLengthto512. Determine if the two results are equal.

zcr_batch = zerocrossrate(y,WindowLength=winLength,OverlapLength=overlap); isequal(zcr_batch,zcr)

ans =logical1