ALISA: An automatic lightly supervised speech segmentation and alignment tool

@article{Stan2016ALISAAA,
  title={ALISA: An automatic lightly supervised speech segmentation and alignment tool},
  author={Adriana Stan and Yoshitaka Mamiya and Junichi Yamagishi and Peter Bell and Oliver Watts and Robert A. J. Clark and Simon King},
  journal={Computer Speech & Language},
  year={2016},
  volume={35},
  pages={116-133}
}
This paper describes the ALISA tool, which implements a lightly supervised method for sentence-level alignment of speech with imperfect transcripts. Its intended use is to enable the creation of new speech corpora from a multitude of resources in a language-independent fashion, thus avoiding the need to record or transcribe speech data. The method is designed so that it requires minimum user intervention and expert knowledge, and it is able to align data in languages which employ alphabetic… CONTINUE READING
10 Citations
51 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 51 references

Similar Papers

Loading similar papers…