An empirical exploration of CTC acoustic models

@article{Miao2016AnEE,
  title={An empirical exploration of CTC acoustic models},
  author={Yajie Miao and Mohammad Gowayyed and Xingyu Na and Tom Ko and Florian Metze and Alexander H. Waibel},
  journal={2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2016},
  pages={2623-2627}
}
The connectionist temporal classification (CTC) loss function has several interesting properties relevant for automatic speech recognition (ASR): applied on top of deep recurrent neural networks (RNNs), CTC learns the alignments between speech frames and label sequences automatically, which removes the need for pre-generated frame-level labels. CTC systems also do not require context decision trees for good performance, using context-independent (CI) phonemes or characters as targets. This… CONTINUE READING
Highly Cited
This paper has 56 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 44 extracted citations

56 Citations

020402015201620172018
Citations per Year
Semantic Scholar estimates that this publication has 56 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 20 references

Similar Papers

Loading similar papers…