This demonstration shows how to combine a 2D CNN, RNN and a Connectionist Temporal Classification (CTC) loss to build an ASR. CTC is an algorithm used to train deep neural networks in speech recognition, handwriting recognition and other sequence problems. CTC is used when we don’t know how the input aligns with the output (how the characters in the transcript align to the audio). The model we create is similar to DeepSpeech2.