TY - GEN
T1 - Automatic phoneme border detection to improve speech recognition
AU - Sergio, Suárez Guerra
AU - Cristian-Remington, Juárez Murillo
AU - Luis, Oropeza Rodríguez José
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - A comparative study of speech recognition performance among systems trained with manually labeled corpora and systems trained with semi-automatically labeled corpora is introduced. An automatic labeling system was designed to generate phoneme labels files for all words within the corpus used to train a system of automatic speech recognition. Speech recognition experiments were performed using the same corpus, first training with manually, and later with automatically generated labels. Results show that the recognition performance is better when the training of selected diccionary, is made with automatic label files than when it is made with manual label files. Not only is the automatic labeling of speech corpora faster than manual labeling, but also it is free from the subjectivity inherent in the manual segmentation performed by specialists. The performance achieved in this work is greater than 96 %.
AB - A comparative study of speech recognition performance among systems trained with manually labeled corpora and systems trained with semi-automatically labeled corpora is introduced. An automatic labeling system was designed to generate phoneme labels files for all words within the corpus used to train a system of automatic speech recognition. Speech recognition experiments were performed using the same corpus, first training with manually, and later with automatically generated labels. Results show that the recognition performance is better when the training of selected diccionary, is made with automatic label files than when it is made with manual label files. Not only is the automatic labeling of speech corpora faster than manual labeling, but also it is free from the subjectivity inherent in the manual segmentation performed by specialists. The performance achieved in this work is greater than 96 %.
KW - ASR applications
KW - Automatic speech segmentation and labeling
KW - Label detection
UR - http://www.scopus.com/inward/record.url?scp=84951986718&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-27060-9_11
DO - 10.1007/978-3-319-27060-9_11
M3 - Contribución a la conferencia
AN - SCOPUS:84951986718
SN - 9783319270593
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 127
EP - 135
BT - Advances in Artificial Intelligence and Soft Computing - 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, Proceedings
A2 - Sidorov, Grigori
A2 - Galicia-Haro, SofÍa N.
PB - Springer Verlag
T2 - 14th Mexican International Conference on Artificial Intelligence, MICAI 2015
Y2 - 25 October 2015 through 31 October 2015
ER -