1 NLP in Thailand by Asanee Kawtrakul Kasetsart University

2  Thailand Language Features  What we do and the problems  The main actors  Research Model and Infrastructure  What do we need more ? Outline

3  Dialects and Tone  Isolating language  Uninflected  Monosyllabic  No word delimiters  Same form but several functions  Same form but several meanings Thai Language Characteristics

4  Grammar coverage  Word formation/Recognition u Compound words vs Sentences u Proper name vs Common noun u Loan word (transliterated foreign words) without special orthography

5 North 18.8% Dialects North-East 34.2% Central 33.7% South 13.3%

6 What do we do?  TEXT PROCESSING  SPEECH PROCESSING  IMAGE PROCESSING

7 Text Processing

8 Text Processing and Problems  Statistical Based Approach  Knowledge Based Approaches  Lack of Legal Corpus  Small Corpus  Lack of Standard(Pos, Semantic Concepts)  Redundancy work

9 Speech Processing  Speech recognition  Speech generation

10 Speech Processing and Problems  Recognition  Generation  Not Only Dialect but Tone  Isolated word not Continuous speech  Word Boundary detection

11 Image Processing  Thai optical character recognition  Hand written recognition

12 OCR and Problems  Isolated Characters

13 The Main Actors  Universities  NECTEC (National Electronic and Computer Technology Center), Ministry of Science and Technology Environment  SIGNLP

14 The Main Actors  More than 50 experienced researchers (minimum 5 years research)  More than 100 young researchers

15 Financial Supporter  National Electronics and Computer Technology Center (NECTEC)  National research council of Thailand (NRCT)  Kasetsart University Research and Development Institute (KURDI)  Thai Research Foundation (TRF)  etc.

16 Research Model and Infrastructure  Short Term  Long Term  Simple But Work  Collaboration between end users, universities and Funding Agency (including Private sectors)  Robust and very large scale  Enlarge the number of researchers

17 What do we need more?  Share resources (Corpus, Dictionary, Tools, etc.)  Share Experiences and Knowledge  Set Big Umbrella and distribute workload  Establish research network  Partnership

18 Conclusion  Most Thai uses Thai Language  Thai Language Processing has good future in the market IF…….

19  We have more Collaborative work  NLP Market for 1/2 of 60 millions