def classify(self, file):
"""
classify given audio file as one of given classes
@param file: audio file object
@return: result of classification
"""
result = {}
current_characteristics = vad(file, frame_size=self.frame_size)
for i in self.used_classes:
result[i] = {}
for j in self.used_characteristics:
result[i][j] = self.probability(i, j, current_characteristics.get(j))
return result
def teach_one_class(self, class_key):
"""
1. method runs VAD for each file which is not classified yet
2. gets all needle characteristics which were set in init method
3. runs teach method for each of characteristics
@param class_key: name of active class of data
"""
words_count = 0
characteristics = self.data_class[class_key]
for i in self.audio_files[class_key]:
if not i.classified:
parameters = vad(i.file_object, frame_size=self.frame_size)
for j in self.used_characteristics:
self.teach(parameters.get(j), characteristics[j])
words_count += parameters.get("words_count")
i.classified = True
self.words_count[class_key] += words_count
