DocumentCode
1725954
Title
Temporal information in tone recognition
Author
Lin, Payton ; Syu-Siang Wang ; Yu Tsao
Author_Institution
Res. Center for Inf. Technol. Innovation, Taipei, Taiwan
fYear
2015
Firstpage
326
Lastpage
327
Abstract
Traditionally, only five components are regarded as having to do with the special characteristics of recognizing tones, while front-end processing and feature extraction have been considered essentially independent. Since mismatch between training and testing in signal-space leads to subsequent distortions in feature-space and model-space, determining whether front-end processing and feature extraction is independent or dependent will be critical for robustness.
Keywords
feature extraction; speech recognition; feature extraction; feature space; front-end processing; model space; signal space; subsequent distortions; temporal information; tone recognition; Amplitude modulation; Feature extraction; Hidden Markov models; Speech; Speech recognition; Testing; Training; temporal features; tone recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics - Taiwan (ICCE-TW), 2015 IEEE International Conference on
Conference_Location
Taipei
Type
conf
DOI
10.1109/ICCE-TW.2015.7216924
Filename
7216924
Link To Document