Summary of the paper
| Title | Automatic Detection of Syllable Boundaries in Spontaneous Speech |
|---|---|
| Authors | Brigitte Bigi, Christine Meunier, Irina Nesterenko and Roxane Bertrand |
| Abstract | This paper presents the outline and performance of an automatic syllable boundary detection system. The syllabification of phonemes is performedwith a rule-based system, implemented in a Java program. Phonemes are categorized into 6 classes. A set of specific rules are developed and categorized as general rules which can be applied inall cases, and exception rules which are applied in some specific situations.These rules deal with a French spontaneous speech corpus.Moreover, the proposed phonemes, classes and rules are listed in anexternal configuration file of the tool (under GPL licence) that make the tool very easy to adapt to a specific corpus by adding or modifying rules, phoneme encoding or phoneme classes, by the use of a new configuration file.Finally, performances are evaluated and compared to 3 other French syllabification systems and show significant improvements. Automaticsystem output and expert's syllabification are in agreement for most of syllable boundaries in our corpus. |
| Language | Corpus (creation, annotation, etc.) |
| Topics | Tools, systems, applications, Phonetic Databases, Phonology, Corpus (creation, annotation, etc.) |
Full paper  |
Automatic Detection of Syllable Boundaries in Spontaneous Speech |
| Bibtex | @InProceedings{BIGI10.219, author = {Brigitte Bigi, Christine Meunier, Irina Nesterenko and Roxane Bertrand}, title = {Automatic Detection of Syllable Boundaries in Spontaneous Speech}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |