A Tool for Cutting Large Speech Corpora: HCI4CS

DOI

10.2991/icaita-16.2016.79How to use a DOI?

Keywords

primi speech; human-computer interaction; speech segmentation

Abstract

There are two methods to cut large speech corpora, include traditional manual segmentation and machine automatic segmentation. The quality of segmentation can be controlled easily using traditional manual segmentation. However, the shortcomings of manual segmentation were also obviously such as inefficiency, high cost. As we all know, the method of machine automatic segmentation has the advantage of high efficiency, but the fussy work to find cutting error can’t be omitted. Thus, this paper developed a tool of human-computer interaction for cutting speech corpora (HCI4CS), which provides segment algorithm, parameter to control, modifying the error of automatic segmentation results and generates labeling files for HTK toolkit. The research object was one thousand speeches of Primi. Using HCI4CS, a person with low cognitive competence about cutting speech corpora can achieve nearly one hundred percent accuracy.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Lin Guo
AU  - Yang Bai
AU  - Jie Su
AU  - Wenlin Pan
AU  - Tianjun Zhang
PY  - 2016/01
DA  - 2016/01
TI  - A Tool for Cutting Large Speech Corpora: HCI4CS
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 320
EP  - 324
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.79
DO  - 10.2991/icaita-16.2016.79
ID  - Guo2016/01
ER  -