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speech-challenge's Introduction

Speech Challenge

TensorFlow Speech Recognition Challenge Kaggle Competition Page

Models

Usage

python3 train.py \
--data_url= \
--model_architecture=deeeep_cnn \
--how_many_training_steps=30000,30000,180000 \
--learning_rate=0.001,0.0001,0.001 \
--batch_size=500 \
--start_checkpoint=speech_commands_train/deeeep_cnn.ckpt-200000

Training Dataset [https://www.kaggle.com/c/tensorflow-speech-recognition-challenge/download/train.7z]

python3 freeze.py \
--model_architecture=deeeep_cnn \
--start_checkpoint=speech_commands_train/deeeep_cnn.ckpt-240000 \
--output_file=graph.pb

python3 label_wav.py \
--graph=graph.pb \
--labels=speech_commands_train/deeeep_cnn_labels.txt \
--wav_dir=test_dataset

Testing Dataset [https://www.kaggle.com/c/tensorflow-speech-recognition-challenge/download/test.7z]

Result

  • example_conv (77%)
  • cnn_trad_fpool3 (77%)
  • esc_cnn (77%)
  • deep_cnn (79%)
  • deeep_cnn (82%)
  • deeeep_cnn (79%)

speech-challenge's People

Contributors

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Watchers

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