Added example data. Added text file and audio file reading.

data/LibriSpeech/dev-clean-wav/3752-4944-0041.txt

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+how delightful the grass smells

data/LibriSpeech/dev-clean-wav/777-126732-0068.txt

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+that boy hears too much of what is talked about here

data/LibriSpeech/test-clean-wav/4507-16021-0019.txt

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+it is the language of wretchedness

data/LibriSpeech/test-clean-wav/7176-92135-0009.txt

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+and i should begin with a short homily on soliloquy

data/LibriSpeech/train-clean-100-wav/1970-28415-0023.txt

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+where people were making their gifts to god

data/LibriSpeech/train-clean-100-wav/211-122425-0059.txt

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+and the two will pass off together

data/LibriSpeech/train-clean-100-wav/2843-152918-0008.txt

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+one day may be pleasant enough but two three four

data/LibriSpeech/train-clean-100-wav/3259-158083-0026.txt

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+i have a nephew fighting for democracy in france

data/LibriSpeech/train-clean-100-wav/3879-174923-0005.txt

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+he must vanish out of the world

main.py

@@ -7,6 +7,15 @@
 import unicodedata
 import re
 
+import tensorflow as tf
+
+import scipy.io.wavfile as wav
+
+DATA_DIR = "data/LibriSpeech/"
+TRAIN_DIR = DATA_DIR + "train-clean-100-wav/"
+TEST_DIR = DATA_DIR + "test-clean-wav/"
+DEV_DIR = DATA_DIR + "dev-clean-wav/"
+
 
 def read_text_file(path):
     """
@@ -88,3 +97,18 @@ def sparse_tuples_from_sequences(sequences, dtype=np.int32):
     shape = np.asarray([len(sequences), np.asarray(indexes).max(0)[1] + 1], dtype=np.int64)
 
     return indexes, values, shape
+
+
+def main(argv):
+    # Read text file.
+    text_file_path = TRAIN_DIR + "211-122425-0059.txt"
+    text = read_text_file(text_file_path)
+    text = normalize_text(text)
+
+    # Read audio file.
+    wav_file_path = TRAIN_DIR + "211-122425-0059.wav"
+    audio_rate, audio_data = wav.read(wav_file_path)
+
+
+if __name__ == '__main__':
+    tf.app.run()