This is my solution for the tensorflow speech recognition challenge on kaggle.

• tensorflow v1.4
• scipy for wave loading
• librosa for audio manipulations
• numpy, pandas
• pyaudio for microphone

The model can be trained using the train.py, all the parameters that can be defined can be found in the parser settings or using python train.py --help.

The file settings1.csv contains a definition of the parameters that will be used to run a particular experiment.

Once the model has been trained, it can be used to predict samples using predict.py, passing the previously generated checkpoints.

The file mic.py is used for real-time recognition, using the microphone and the pyAudio library.