-(rate, sig) = wav.read(sys.stdin.buffer)
-data = mfcc(sig, rate, winlen
-for i in model.predict(dat, batch_size=32, verbose=0):
- print(i[0])
+(rate, sig) = wav.read(sys.argv[2], mmap=True)
+data = mfcc(sig, rate, winlen, winstep, numcep=13, appendEnergy=True)
+tgob = pympi.TextGrid(xmax=winstep*len(data))
+tier = tgob.add_tier('lyrics')
+
+time = 0.0
+lastlabel = False
+lasttime = 0.0
+for i in model.predict(data, batch_size=32, verbose=0):
+# print('{}\t{}'.format(time, i))
+ label = i > 0.5
+ if label != lastlabel and time-lasttime > 0.5:
+ tier.add_interval(lasttime, time, '*' if lastlabel else '')
+ lastlabel = label
+ lasttime = time
+
+ time += winstep
+tgob.to_file('/dev/stdout')