Exemplo n.º 1
0
	def __init__(self, learning_rate=0.1, train="keys_Training.sdo",
			cv="keys_CV.sdo", test="keys_Test.sdo"):
		print "Loading data sets"
		self.train_data = Network.parseSdo(SoundDataObject.loadSdo(train))
		self.cv_data = Network.parseSdo(SoundDataObject.loadSdo(cv))
		self.test_data = Network.parseSdo(SoundDataObject.loadSdo(test))
		print "Done loading"
		self.build_mlp(learning_rate, len(self.train_data["Y"][0]))
Exemplo n.º 2
0
 def __init__(self,
              learning_rate=0.1,
              train="keys_Training.sdo",
              cv="keys_CV.sdo",
              test="keys_Test.sdo"):
     print "Loading data sets"
     self.train_data = Network.parseSdo(SoundDataObject.loadSdo(train))
     self.cv_data = Network.parseSdo(SoundDataObject.loadSdo(cv))
     self.test_data = Network.parseSdo(SoundDataObject.loadSdo(test))
     print "Done loading"
     self.build_mlp(learning_rate, len(self.train_data["Y"][0]))
Exemplo n.º 3
0
	def _getSdo(self, name, max_samples, labelCombos):
		sdo = SoundDataObject(name)
		for i in range(min(max_samples, len(labelCombos))):
			#use sound syns to get label and signal
			labels = [label for label in labelCombos[i]]
			syns = SoundSyns()
			for key in labels:
				syns.add_key(key)
			#get buckets
			decomp = SoundDecomposer(name)
			decomp.readSignal(SoundSyns.rate, syns.signal)
			#add buckets to sdo
			sdo.addDataSingle(Sample(decomp.freqBuckets, labels))
		return sdo
Exemplo n.º 4
0
from sound_data_object import SoundDataObject
from sound_syns import SoundSyns

sdo = SoundDataObject("test")
sdo.save()

newSdo = SoundDataObject.loadSdo("test")