  Connectionist temporal classification (CTC) has matured as an alignment free
to sequence transduction and shows competitive for end-to-end speech
recognition. In the CTC topology, the blank symbol occupies more than half of
the state trellis, which results the spike phenomenon of the non-blank symbols.
For classification task, the spikes work quite well, but as to the segmentation
task it does not provide boundaries information. In this paper, a novel
topology is introduced to combine the temporal classification and segmentation
ability in one framework.
