I have some audio data loaded in a numpy array and I wish to segment the data by finding silent parts, i.e. parts where the audio amplitude is below a certain threshold over
another way to do this quickly and concisely:
import pylab as pl
v=[0,0,1,1,0,0,1,1,1,1,1,0,1,0,1,1,0,0,0,0,0,1,0,0]
vd = pl.diff(v)
#vd[i]==1 for 0->1 crossing; vd[i]==-1 for 1->0 crossing
#need to add +1 to indexes as pl.diff shifts to left by 1
i1=pl.array([i for i in xrange(len(vd)) if vd[i]==1])+1
i2=pl.array([i for i in xrange(len(vd)) if vd[i]==-1])+1
#corner cases for the first and the last element
if v[0]==1:
i1=pl.hstack((0,i1))
if v[-1]==1:
i2=pl.hstack((i2,len(v)))
now i1 contains the beginning index and i2 the end index of 1,...,1 areas