python语音识别训练_Tensorflow：如何在j语言中使用python训练的语音识别模型

{/strong>在生成一个基于python的应用程序后，需要一个经过训练的应用程序生成的图形。

为此，我查看了下面的example。但是我不明白的是如何收集我的输出。我知道我需要为图形提供3个输入。在

从官方教程中给出的示例中，我阅读了基于python的代码。在def run_graph(wav_data, labels, input_layer_name, output_layer_name,

num_top_predictions):

"""Runs the audio data through the graph and prints predictions."""

with tf.Session() as sess:

# Feed the audio data as input to the graph.

# predictions will contain a two-dimensional array, where one

# dimension represents the input image count, and the other has

# predictions per class

softmax_tensor = sess.graph.get_tensor_by_name(output_layer_name)

predictions, = sess.run(softmax_tensor, {input_layer_name: wav_data})

# Sort to show labels in order of confidence

top_k = predictions.argsort()[-num_top_predictions:][::-1]

for node_id in top_k:

human_string = labels[node_id]

score = predictions[node_id]

print('%s (score = %.5f)' % (human_string, score))

return 0

有人能帮我理解TensorFlowJavaAPI吗？在