Loading...

Automatic Labeling of Prosody in Persian Unmarked Speech

Jamshidlou, Paria | 2014

671 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 45438 (31)
  4. University: Sharif University of Technology
  5. Department: Languages and Linguistics Center
  6. Advisor(s): Eslami, Moharram; Bahrani, Mohammad
  7. Abstract:
  8. Prosodic annotations are used for locating and characterizing prominent parts in utterances as well as identifying and describing boundaries of coherent stretches of speech. Automatic detection and labeling of prosodic events in speech has received much attention in recent years since prosody is intricately bound to the semantics of the utterance. Recognition of prosodic events is important for spoken language applications such as automatic understanding and translation of speech. Moreover, corpora labeled with prosodic markers are essential for building speech synthesizers that use data-driven approaches to generate natural speech. Such databases are important to reach a better understanding of prosodic phenomena, and essential for various applications of prosody in the area of speech technology.
    In this work, we introduce two various models including syntactic and acoustic models for labeling prosody events in unmarked Persian mode. These models can recognize the type and place of prosody events using ToBI. HMM-based acoustic model predicts prosody from acoustic observations. In the second model, prosody is assigned based on syntactic information extracted from text. The results show that using acoustic and syntactic models for prosody labeling has accuracy of 87.9 and 96.1 respectively. The results of this thesis can be used in speech synthesis and speech understanding systems as well as in preparing annotated speech database
  9. Keywords:
  10. Hidden Markov Model ; Prosody Labeling ; Unmarked Speech ; Acoustic Model ; Syntactic Model ; Obligatory Contour Principle

 Digital Object List

 Bookmark