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HREF="node4.html">Contents</A></B>
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<B> <A ID="tex2html1230"
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HREF="node201.html">Index</A></B>
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<H1><A ID="SECTION00760000000000000000">
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Event detection</A>
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</H1>
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<P>
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Besides taking snapshots, a second mode of passing information from
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audio signals to control computations is
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<A ID="3634"></A>
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<I>event detection</I>.
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Here we derive time information from the audio signal. An example
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is
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<A ID="3636"></A><I>threshold detection</I>,
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in which the input is an audio signal and the output is a time sequence.
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We'll consider the example of threshold detection in some detail here.
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<P>
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A
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typical reason to use threshold detection is to find out when
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some kind of activity starts and stops, such as a performer playing
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an instrument. We'll suppose we already have a continuous measure of activity
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in the form of an audio signal. (This can be done, for example, using an
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<A ID="3638"></A><I>envelope follower</I>). What we want is a pair of time sequences, one which
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marks times in which activity starts, and the other marking stops.
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<P>
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<DIV ALIGN="CENTER"><A ID="fig03.07"></A><A ID="3642"></A>
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<TABLE>
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<CAPTION ALIGN="BOTTOM"><STRONG>Figure 3.7:</STRONG>
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Threshold detection: (a) with no debouncing; (b) debounced using two
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threshold levels; (c) debounced using dead periods.</CAPTION>
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<TR><TD><IMG
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WIDTH="413" HEIGHT="551" BORDER="0"
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SRC="img331.png"
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ALT="\begin{figure}\psfig{file=figs/fig03.07.ps}\end{figure}"></TD></TR>
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</TABLE>
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</DIV>
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<P>
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Figure <A HREF="#fig03.07">3.7</A> (part a) shows a simple realization of this idea.
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We assume the signal input is as shown in the continuous graph. A horizontal
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line shows the constant value of the threshold. The time sequence marked
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"onsets" contains one event for each time the signal crosses the threshold
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from below to above; the one marked "turnoffs" marks crossings in the other
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direction.
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<P>
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In many situations we will get undesirable onsets and turnoffs
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caused by small ripples in the signal close to the threshold. This is
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avoided by
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<A ID="3646"></A><I>debouncing</I>,
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which can be
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done in at least two simple ways. First, as shown in part (b) of the figure,
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we can set two thresholds: a high one for marking onsets, and a lower one for
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turnoffs. In this scheme the rule is that we only report the first onset after
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each turnoff, and, <I>vice versa</I>, we only report one turnoff after each onset. Thus
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the third time the signal crosses the high threshold in the figure, there is
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no reported onset because there was no turnoff since the previous one. (At
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startup, we act as if the most recent output was a turnoff, so that the first
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onset is reported.)
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<P>
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A second approach to filtering out multiple onsets and turnoffs, shown in
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part (c) of the figure, is to associate a <I>dead period</I> to each onset.
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This is a constant interval of time after each reported onset, during which
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we refuse to report more onsets or turnoffs. After the period ends, if
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the signal has dropped below the threshold in the meantime, we belatedly
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report a turnoff. Dead periods may also be associated with turnoffs, and the
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two time periods may have different values.
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<P>
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The two filtering strategies may be used separately or simultaneously. It
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is usually necessary to tailor the threshold values and/or dead
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times by hand to each specific situation in which thresholding is used.
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<P>
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Thresholding is often used as a first step in the design of higher-level
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strategies for arranging computer responses to audible cues from performers.
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A simple example could be to set off a sequence of pre-planned processes, each
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one to be set off by an onset of sound after a specified period of relative
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silence, such as you would see if a musician played a sequence of phrases
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separated by rests.
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<P>
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More sophisticated detectors (built on top of threshold detection) could detect
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continuous sound or silence within an expected range of durations, or sequences
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of quick alternation between playing and not playing, or periods of time in
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which the percentage of playing time to rests is above or below a threshold, or
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many other possible features. These could set off predetermined reactions or
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figure in an improvisation.
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<P>
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