DocumentCode :
1060233
Title :
Automatic Prosodic Variations Modeling for Language and Dialect Discrimination
Author :
Rouas, Jean-Luc
Author_Institution :
Inst. de Engenharia de Sistemas e Comput., Lisbon
Volume :
15
Issue :
6
fYear :
2007
Firstpage :
1904
Lastpage :
1911
Abstract :
This paper addresses the problem of modeling prosody for language identification. The aim is to create a system that can be used prior to any linguistic work to show if prosodic differences among languages or dialects can be automatically determined. In previous papers, we defined a prosodic unit, the pseudosyllable. Rhythmic modeling has proven the relevance of the pseudosyllable unit for automatic language identification. In this paper, we propose to model the prosodic variations, that is to say model sequences of prosodic units. This is achieved by the separation of phrase and accentual components of intonation. We propose an independent coding of those components on differentiated scales of duration. Short-term and long-term language-dependent sequences of labels are modeled by n-gram models. The performance of the system is demonstrated by experiments on read speech and evaluated by experiments on spontaneous speech. Finally, an experiment is described on the discrimination of Arabic dialects, for which there is a lack of linguistic studies, notably on prosodic comparisons. We show that our system is able to clearly identify the dialectal areas, leading to the hypothesis that those dialects have prosodic differences.
Keywords :
speech processing; Arabic dialects; automatic language identification; automatic prosodic variations modeling; dialect discrimination; language discrimination; language identification; language-dependent sequences; spontaneous speech; Acoustics; Automatic testing; Decoding; Helium; Humans; Loudspeakers; NIST; Natural languages; Speaker recognition; Speech analysis; Automatic language identification (ALI); prosody; read and spontaneous speech;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2007.900094
Filename :
4276764
Link To Document :
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