Automatic cognitive load detection from speech features
OZCHI '07 Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces
Language and variety verification on broadcast news for Portuguese
Speech Communication
Application of prosody models for developing speech systems in Indian languages
International Journal of Speech Technology
A hierarchical language identification system for Indian languages
Digital Signal Processing
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A novel approach of combining cepstral features and prosodic features in language identification is presented in this paper. This combination approach shows a significant improvement on a GMM-UBM based language identification (LID) system which utilizes modern shifted delta cepstrum (SDC) and feature warping techniques. The proposed system achieves a high accuracy of 87.1% on a 10-language task, and outperforms the baseline system by 12%. The prosodic features are proven to be very effective in both tonal and non-tonal LID, as they deliver new language-discrimination information in addition to those from widely used cepstral features. Additionally, the performance of MFCC and PLP features with different coefficient numbers in language identification tasks are researched and compared. Less number of coefficients is more likely to be sufficient or even better for language identification.