Connectionist Temporal Classification (CTC) is a combination of an algorithm and a loss function that transform a sequence of acoustic sounds into a sequence of letters, i.e., speech recognition. Unlike the encoder-decoder structure which transforms a longer input sequence to a shorter output sequence, CTC first transforms the input sequence to an equal length sequence, then transforms the alignment to a shorter output sequence by merging consecutive duplicates and removing blanks. The output vector of the first step is called alignment, and the transformation in second step is called collapsing function.