def sample(config, params, load_path, part):
data = Data(**config['data'])
recognizer = SpeechRecognizer(data.recordings_source,
data.labels_source,
data.eos_label,
data.num_features,
data.num_labels,
character_map=data.character_map,
name='recognizer',
**config["net"])
recognizer.load_params(load_path)
dataset = data.get_dataset(part, add_sources=(data.uttid_source, ))
stream = data.get_stream(part,
batches=False,
shuffle=False,
add_sources=(data.uttid_source, ))
it = stream.get_epoch_iterator()
print_to = sys.stdout
for number, data in enumerate(it):
print("Utterance {} ({})".format(number, data[2]), file=print_to)
groundtruth_text = dataset.pretty_print(data[1])
print("Groundtruth:", groundtruth_text, file=print_to)
sample = recognizer.sample(data[0])['outputs'][:, 0]
recognized_text = dataset.pretty_print(sample)
print("Recognized:", recognized_text, file=print_to)
def sample(config, params, load_path, part):
data = Data(**config['data'])
recognizer = SpeechRecognizer(
data.recordings_source, data.labels_source,
data.eos_label, data.num_features, data.num_labels,
character_map=data.character_map,
name='recognizer', **config["net"])
recognizer.load_params(load_path)
dataset = data.get_dataset(part, add_sources=(data.uttid_source,))
stream = data.get_stream(part, batches=False, shuffle=False,
add_sources=(data.uttid_source,))
it = stream.get_epoch_iterator()
print_to = sys.stdout
for number, data in enumerate(it):
print("Utterance {} ({})".format(number, data[2]), file=print_to)
groundtruth_text = dataset.pretty_print(data[1])
print("Groundtruth:", groundtruth_text, file=print_to)
sample = recognizer.sample(data[0])['outputs'][:, 0]
recognized_text = dataset.pretty_print(sample)
print("Recognized:", recognized_text, file=print_to)
