Experiments on Automatic Language Identification for Philippine Languages using Acoustic Gaussian Mixture Models

被引：0
|
作者：
Laguna, Ann Franchesca [1 ]
Guevara, Rowena Cristina [1 ]
机构：
[1] Univ Philippines Diliman, Digital Signal Proc Lab, Quezon City, Philippines
来源：
2014 IEEE REGION 10 SYMPOSIUM | 2014年
关键词：
Language Identification; Acoustic; Philippine Languages; GMM;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A Philippine LID system has not been previously created because of the limited amount of recorded speech data. This research initiates the LID research using the Philippine Language Database (PLD) collected by the Digital Signal Processing Laboratory of the University of the Philippines Diliman (DSP-UPD). Mel Frequency Cepstral Coefficients (MFCC), Perceptual Linear Prediction (PLP), Shifted Delta Cepstra (SDC) and Linear Predictive Cepstral Coefficients (LPCC) features are extracted from the speech segments. Gaussian Mixture Model (GMM) using Expectation Maximization (EM) and Universal Background Model (UBM) approach is used to model the acoustic characteristics of the language. Maximum a Posteriori (MAP) probability is then used to determine the language of a speech utterance based on the language GMMs. PLP using a 16 Mixture GMM-EM has been found to produce the best performance among the four feature vectors in discriminating the languages.
引用
收藏
页码：657 / 662
页数：6
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