Title
A Bag-Of-Phonemes Model For Homeplace Classification Of Mandarin Speakers
Abstract
Mandarin, also known as Standard Chinese is the official language of China and Singapore, there are certain differences when mandarin is spoken by people from different homeplaces. The homeplace classification is important in speech recognition and machine translation. In this paper, we proposed a novel model named Bag-of-phonemes (BOP) for homeplace classification of mandarin speakers, which follows the conceptually similar idea of the Bag-of-words (BOW) model in text processing. The low-level Mel-frequency cepstral coefficients (MFCC) speach features of each homeplace are clustered into a set of codewords referred to as phonemes. With this codebook, each speech signal can be represented by a feature vector of distribution on phonemes. Classical classifiers such as support vector machine (SVM) can be applied for classification. This model is tested by RASC863 database, empirical studies show that the new model has a better performance on the RASC863 database comparing to previous works [1].
Year
DOI
Venue
2015
10.1007/978-3-319-19390-8_76
PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2015)
Keywords
Field
DocType
Bag-of-words, Bag-of-phonemes, Mandarin accents
Bag-of-words model,Mel-frequency cepstrum,Feature vector,Standard Chinese,Pattern recognition,Computer science,Support vector machine,Machine translation,Speech recognition,Artificial intelligence,Mandarin Chinese,Text processing
Conference
Volume
ISSN
Citations 
9117
0302-9743
0
PageRank 
References 
Authors
0.34
6
4
Name
Order
Citations
PageRank
Hanqing Zhao145.83
Zengchang Qin243945.46
Yiyu Wang300.34
Yuxiao Wang400.34