Applied Speech and Audio Processing: With matlab examples
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Applied Speech and Audio Processing With MATLAB Examples ( PDFDrive )
4.5. Auditory scene analysis
77 Figure 4.6 Illustration of the feature of proximity. Two sequences of alternating tones are shown. In plot (a) the absolute time difference between like tones is short, thus they exhibit closer proximity compared to the larger time difference between like tones in plot (b). basic principles [26,27] which relate complex sounds and sequences to perception, and which we will consider in the following subsections. 4.5.1 Proximity Sounds of similar proximity are those that are close in terms of amplitude, pitch, duration, timbre, and so on. There is definitely a tendency for the brain to classify similar sounds as belonging to the same parts of an auditory scene. For example, when listening to a recording of a wind quartet, the brain would probably be correct in assuming that each oboe-like sound originates from the same oboe. If, in fact, two oboes are playing, then that may only become evident when both play different notes simultaneously. We shall use Matlab code to generate two sound sequences, each consisting of two alternating tones. One first sequence plays the tones slowly, the other sequence plays them quickly. The sequences are illustrated in Figure 4.6 showing a closer proximity in the upper plot compared to the lower, due to increased gap between similar frequencies in the latter. A rather simple Matlab demonstration, using the tonegen function of Section 2.7.1, can illustrate this point: ss=0.1; %short sound length in seconds ls=0.4; %long sound length in seconds Fs=8000; %sample rate short_a=tonegen(440,Fs,ss); %concert A4 78 Hearing short_b=tonegen(932,Fs,ss); %B5 long_a=tonegen(440,Fs,ls); long_b=tonegen(932,Fs,ls); %Construct alternating sounds in a single matrix short_mat=[short_a, short_b]; long_mat=[long_a, long_b]; %Repeat this matrix several times long=repmat(long_mat,1,3); short=repmat(short_mat,1,12); The two tone sequences reside in vectors long and short respectively. Let us begin by listening to the long duration tones: soundsc(long, Fs); Most likely this is heard as a single sequence consisting of two tones. However, when listening to the faster sequence of short duration tones, it is more likely that listeners notice two streams of sound – one high frequency, and one low frequency, but both are pulsed: soundsc(short, Fs); To explain, both sequences exhibit no gaps between tones, thus there is close temporal proximity between an A 4 and the following B 5 . Although there is not a great pitch proximity between the A 4 and the B 5 (which is slightly over an octave higher), in the slower sequence, the close temporal proximity dominates, leading the brain to associate the tones together into one slow string. In the faster sequence, however, the proximity of the like notes is increased – they are now only 100 ms apart – and thus the proximity of one A 4 to the next is increased over the slow sequence. Likewise, each B 5 is nearer to the next one. In this recording, the close tonal proximity dominates, and thus two separate streams are heard. One is of beeping A 4 notes and one is of beeping B 5 notes. 4.5.2 Closure The closure principle allows the brain to fill any auditory ‘gaps’ to match its expectations regarding continuity, origin, and so on. This is also known as auditory induction since our brains do not just deduce the presence of missing audio, but actually induce a replacement to cover the missing gaps. It seems our brains dislike sounds that do not fit into an ongoing scene interpretation, to the extent that additional material will be created to bring the user perceived audio in line with brain expectations. The same process is involved with images, and is the basis for many optical illusions, from impossible three-dimensional shapes, to discovering hidden faces within abstract images. |
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