• 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