  This paper proposes a novel approach to create an unit set for CTC based
speech recognition systems. By using Byte Pair Encoding we learn an unit set of
an arbitrary size on a given training text. In contrast to using characters or
words as units this allows us to find a good trade-off between the size of our
unit set and the available training data. We evaluate both Crossword units,
that may span multiple word, and Subword units. By combining this approach with
decoding methods using a separate language model we are able to achieve state
of the art results for grapheme based CTC systems.
