Title :
Temporal information in tone recognition
Author :
Lin, Payton ; Syu-Siang Wang ; Yu Tsao
Author_Institution :
Res. Center for Inf. Technol. Innovation, Taipei, Taiwan
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;
Conference_Titel :
Consumer Electronics - Taiwan (ICCE-TW), 2015 IEEE International Conference on
Conference_Location :
Taipei
DOI :
10.1109/ICCE-TW.2015.7216924