University of Bahrain

Transcription

1 University of Bahrain College of Engineering Dept of Electrical and Electronics Engineering Experiment 5 EEG 453 Multimedia Audio processing Objectives This experiment demonstrates different Audio processing techniques using MATLAB Laboratory Procedure Audio signals, much like images, can undergo filtering. It is somewhat easier to understand the impact of signal processing on audio, since audio needs not be translated from a spatial to a frequency domain. PART -I 1.1 To load a wave (PCM) audio file, Matlab provides the function wavread : music = wavread('music.wav'); It's important to capture the sampling frequency at which the sound was recorded, otherwise the speed of playback and results of further processing is not guaranteed to be correct:

2 [music, f] = wavread('music.wav'); To play a wave file at sampling frequency f: wavplay(music, f); To view the waveform, plot the wave. Since audio is represented with many thousand samples per second, it may be required to plot small portions of the waveform at a time. subplot(2,1,1), plot(music), title('entire waveform'); smallrange = : floor(f/100); subplot(2,1,2), plot(smallrange, music(smallrange)), title('100 milliseconds'); 1.2. Spectrogram 2-dimensional plots of audio waves can be used to easily identify magnitude; however, combined frequency distributions and magnitudes are more easily viewed in a spectrogram: specgram(music, 512, f); where 512 is the number of samples that are used for the discrete Fourier Transform, and thus a grouping factor of samples per column in the spectrogram image.

3 Plotting both the original waveform and the spectrogram, it is possible to find correspondences between the two graphical representations:

4 However, it is easier to find such similarities in smaller portions of audio. We can also find repeating patters: subplot(2,1,1), plot(music(100000:150000)), axis('tight'); subplot(2,1,2), specgram(music(100000:150000),128,f); 2.1.Filtering We will examine audio filtering in the sense of specific frequency suppression and extraction. There are many different types of filters available for the construction of filters. We will specifically use the Butterworth filter. Matlab includes function butter for building Butterworth filters of three sorts: 'low' : Low-pass filters, which remove frequencies greater than some specified value. 'high' : High-pass filters, which remove frequencies lower than some specified value. 'stop' : Stop-band filters, which remove frequencies in a given range of values. Frequencies values are specified in normalized terms between 0.0 and 1.0, where 1.0 corresponds to half the sampling frequency: f/2. A given frequency is thus expressed in terms of this value, for example, 1000Hz = 1000/(f/2). Filters are described in terms of 2 vectors ([b, a] = [numerator, denominator]).

5 To apply a filter to a 1-D audio waveform, Matlab provides function filtfilt, which takes as arguments the result [b, a] from butter, the waveform, and a value denoting the order (number of coefficients) of the filter. A filter's frequency response can be plotted using function freqz. Magnitude values at zero db are unaffected by the filter. Magnitude values below 0 db are suppressed Low-pass filter We design a 10th order low-pass filter to supress frequencies higher than 200Hz. fnorm = 200 / (f/2); [b,a] = butter(10, fnorm, 'low'); musiclow = filtfilt(b, a, music); The frequency response for this filter: freqz(b,a,128,f); wavplay(musiclow,f); Playing the new audio waveform clearly reveals that low (bass) frequencies are preserved, while all higher frequencies have been suppressed.

6 2.1.2 High-pass filter We design a 10th order high-pass filter to supress frequencies below 5kHz. fnorm = 5000 / (f/2); [b, a] = butter(10, fnorm, 'high'); musichigh = filtfilt(b, a, music); The frequency response of this filter freqz(b,a,128,f); wavplay(musichigh,f); Playing the new audio waveform reveals only high-pitched tones Stop-band filter fnorm = [500/(f/2), 2500/(f/2)]; [b, a] = butter(10, fnorm, 'stop'); musicband = filtfilt(b, a, music); The frequency response for this filter freqz(b,a,128,f); wavplay(musicband,f);

7 Part -II Recording Audio To record data from an audio input device (such as a microphone connected to your system) for processing in MATLAB: 1. Create an audiorecorder object. 2. Call the record or recordblocking method, where: record returns immediate control to the calling function or the command prompt even as recording proceeds. Specify the length of the recording in seconds, or end the recording with the stop method. Optionally, call the pause and resume methods. recordblocking retains control until the recording is complete. Specify the length of the recording in seconds. 3. Create a numeric array corresponding to the signal data using the getaudiodata method. For example, connect a microphone to your system and record your voice for 5 seconds. Capture the numeric signal data and create a plot: % Record your voice for 5 seconds.

8 recobj = audiorecorder; disp('start speaking.') recordblocking(recobj, 5); disp('end of Recording.'); % Play back the recording. play(recobj); % Store data in double-precision array. myrecording = getaudiodata(recobj); % Plot the samples. plot(myrecording); Create an audiorecorder object for CD-quality audio in stereo, and view its properties: recobj = audiorecorder(44100, 16, 2); get(recobj) %Collect a sample of your speech with a microphone, and plot the signal data: % Record your voice for 5 seconds. recobj = audiorecorder; disp('start speaking.') recordblocking(recobj, 5); disp('end of Recording.'); % Play back the recording. play(recobj); % Store data in double-precision array. myrecording = getaudiodata(recobj); % Plot the waveform. plot(myrecording);

9 PART III Create a WAV file of your own audio voice, and read portions of the file back into MATLAB. % Create WAV file in current folder. %Record your own voice, name the file as myfile and place it in current folder hfile = 'myfile.wav'; % Read the data back into MATLAB, and listen to audio. [y, Fs, nbits, readinfo] = wavread(hfile); sound(y, Fs); % Pause before next read and playback operation. duration = numel(y) / Fs; pause(duration + 2) % Read and play only the first 2 seconds. nsamples = 2 * Fs; [y2, Fs] = wavread(hfile, nsamples); sound(y2, Fs); pause(4) % Read and play the middle third of the file. sizeinfo = wavread(hfile, 'size'); tot_samples = sizeinfo(1); startpos = tot_samples / 3; endpos = 2 * startpos; [y3, Fs] = wavread(hfile, [startpos endpos]); sound(y3, Fs);