ࡱ> c DjbjbSS 411]( ( ( ( ( ( ( 4 4 l Yh ,Y( ( (  .( ( \ ( ( ( ( 6( ( b LT? Issues in the French-English-Thai Dictionary Project Mathieu LAFOURCADE LIRMM 161, rue Ada 34392 Montpellier Cedex 5 France Tel. (+33) 04.67.41.85.71 Fax. - 85.00 email: Mathieu.Lafourcade@lirmm.frWanchai RIVEPIBOON Software Eng. Lab. Dept. of Comp. Eng. Faculty of Eng. Chulalongkorn University Bangkok 10330 Thailand Tel.(66-2) 218 6988 Fax. - 215 6955 email Wanchai.R@chula.ac.th (last revision September 1998) Abstract This paper first presents some issues in the FET project, which aims at building a French-English-Thai dictionary. This project started from the results of a previous French-English-Malay dictionary achieved in July 1996. Specificities of Thai were the origin of problems linked to writing systems, orthographic transcriptions, and phonetic transcriptions. We also explored what could be the desirable form of multilingual electronic dictionaries. Keywords Multilingual dictionaries, dictionary construction, dictionary services, tools and servers, orthographic transcription, phonetic transcription. Introduction A multilingual (known as FeT for French-English-Thai) dictionary construction project is the occasion to present and analyze some problems linked to Thai and issues for the dictionary (1) construction and (2) electronic distribution. We will not detail here the aspects concerning the printed format production and distribution. This project inherited the results (both data and methodology) of a French-English-Malay project achieved in July 1997 [2]. We are targeting two kinds of dictionaries. The first one is a general dictionary of about 20.000 entries (around 50.000 word senses), containing information about the pronunciation (both French and Thai), the word category, the gender, some meaning refinement, some phrases and locutions (more than 11.000) and some sentence examples (more than 3.000). Novice learners (Thai and French) should be able to use this dictionary with ease and profit. The second type of dictionary [4] is a lexicon in computer science terminology (also trilingual). It contains roughly 5.000 entries in each language, with category and pronunciation but without examples, nor locutions. Thai and its encoding made the transcription aspects crucial. Furthermore, we had to deal with the production of the phonetic transcription of the Thai equivalents. These transcriptions are needed for the end-user to figure out segmentation and pronunciation of Thai. They are also instrumental during the building phase of the dictionary, as we worked in a heterogeneous environment (Windows and MacOS). This paper first presents the methodology we adopted for the construction of these dictionaries. As (1) dictionary building is a complex collaborative project and (2) computer resources were scarce, we have deliberately taken a low technical level approach by not using specialized tools. On the other side, for the electronic distribution, we investigated (quite) high technical solutions. For this second project phase, we present different kinds of dictionary services we developed to make lexical resources accessible and exploitable to end-users. 1. Multilingual dictionary construction a. English Centered Multilingual Fork dictionaries The inclusion of English equivalents, as a second source language, among the source language (French in our case) and the other target languages (Malay, Thai, etc.), is crucial for lexicographers to reduce error risks when producing equivalent translations in target languages. Moreover, it is often quite difficult to find lexicographers having a very deep knowledge of French in countries which have not been during their history especially exposed to French (contrary to Vietnam, for instance). The presence of English translation is thus a worthy mine of information. A fork dictionary associates to each work meaning (also called word acceptation) of the source language, one or several meanings in the target language. It is the usual structure of bilingual dictionary, but it is in our case extended for several target languages.  Figure 1. Fork multilingual dictionary structure. The first meaning is the more general and may not be linked to one or several glosses. Other meaning correspond to glosses, labels or different categories. As a general schema, a French entry (the source language) is divided into several meanings by the help of glosses, labels or categories. A given entry can contain subentries (generally pronominal verbs). For a given meaning, several equivalents for each target languages and optionally some sentence examples or locutions. In annex (figure 3), we give a sample for a French-English-Thai dictionary, with the type of each field. For each target language, equivalents are grouped into independent blocks. We consider for each French meaning, an equivalent block for English and Thai. Each of these blocks can refine their meaning by the use of glosses or labels in target languages. Target languages glosses are to be opposed to source language glosses, which fork meaning for target languages. Target language glosses do not interfere among each other. Thus, by keeping blocks independent, we can read the dictionary from the source language to one target language (by filtering out alternative target languages). b. Word meanings segmentation by glosses and Thai language issues When there are several acceptations for one French word, we tend to associate one entry to one acceptation. In fact, it is basically a lexicographer choice to split (or not) a given word into several entries if more than one meanings are recognized. Inside one given acceptation, we use glosses for refinement in the source language and in target languages. In case of contrastive phenomena, a gloss allows one to differentiate the meaning in the target language. For example, there are three possible equivalents for rice in Malay : padi (the rice still in the field), beras (not husked rice) and nasi (cooked rice). Labels do participate to meaning refinement, but are more used to indicate some usage context (as agric. for agriculture) or added information (as abrv. for abbreviation or as vx. for old). Labels take their values into a finite set, contrary to glosses, which are open. In Thai, there are many language levels: they can range from crude, informal to polite or by used in specific context such as religious or royalty matters. For example, for the verb to eat, we can have " "  rapathan (very polite), "  thaan (polite),   kin (informal), ! sawreu (only for the royal family),   chan (only for monk), derk (slang). We need, then, to include these information in the Thai equivalent block by the inclusion of specific Thai labels. Another issue is the gap between cultural aspects between French and Thai. Generally speaking, hypocrisy has a negative connotation in Western culture, but is considered as the ground for politeness in Thailand with a strong positive emphasis. When needed, this kind of information can be indicated as glosses. c. Construction methodology Lexicographers used standard word processors (as Microsoft Word"!) to complete dictionary entries. For each field type, we associate a unique typographic style. This allows us both to ease the lexicographer work and to make possible the data conversion between various formats without losing the entry structure. Also worth noting, the use of typographic attributes reduces risks of logical type confusion compared to a labeled plain text approach. For the FeT project, Thai equivalent blocks are added next to Malay equivalent blocks. Moreover, for each Thai equivalent, we add a phonetic transcription readable for French speakers). Such transcriptions already exist, but not one seems to be (1) either complete (2) nor adapted to our needs (3) nor easily readable. We are currently specifying such a transcription that will be readable for a French reader. It must also include word separators, as Thai writing does not provide for something equivalent to space character. In the working files, we will keep Malay in parallel with Thai, which is often useful for coherence checking. In the printed version, Malay will not be included, nor English, but both will still be accessible in computer versions. During the building phase of the dictionary, we use a transcription free from all special characters and no special formatting. This allows us to freely exchange data between various systems and codings (MacOS, Windows and UNIX) through networks. For instance, the French word dictionnaire (dictionary) will be transcripted ^phot_ja-na=^nou-krom ( "). This transcription is readable for French speakers and relatively faithful to Thai pronunciation (it includes tones). We are also currently designing other non-ambiguous transcriptions more adapted to English speakers (and others) and tools for automatic conversion among various transcriptions. We also added a word separator (the /) for Thai equivalents in their orthographic form. The printed dictionary will not included them, but the electronic version will allow the user to display them. This is very useful to newcomers to the Thai language in case of composed words, phrases and sentences.  Figure 2. Major processing stages in the Fe* dictionary production. From the RTF files (produced by lexicographers), we can derive several formats for several tools. Saved as RTF (Rich Text Format), the working files are imported in a database system (Fourth Dimension), where some checking and counting can be easily undertaken. This project phase is done and controlled by computer scientists (such a task would not likely be taken over by lexicographers). From the database various output formats can be produced. For instance: DDDDDDDDDDDDNDDDDDDDDNDDDDNDDDDDDDDDNDDDNDDDDDDDDDDDDNDDDDDDDDDDDDNDDDDDDDDDDDDDNDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD" a Microsoft Word"! source, dully formatted and compacted which feeds a PageMaker"! document for the printed version production (with a professional page layout); " a Microsoft Help"! source, allowing us to produce a (very basic) electronic version of the dictionary on Windows. This dictionary can be viewed with the Microsoft Help Viewer"!; " a DOP source allowing us to obtain an advanced electronic version of the dictionary on MacOS. This FICUS tool (see thereafter) using the DOP format allows the user to filter out information, to sort and count them, ). The same DOP database can be used for making the dictionary available through the Internet (either by the Web or by e-mail). During this project, several observations have been made. First, lexicographers prefer to work with standard software packages widely available like word processors more than Databases. Basic operations (like cutting, pasting, printing, word counting, ) seem more versatile in word processors than database engines. Also, word processors offer a high visibility of entry contexts. With or without reasons, database systems do not constitute the privileged tool of linguists. Secondly, for technical, management and relational reasons, version management packages are generally not suited to large lexicographic projects. One person should be clearly identified as the repository of the reference state of the development of dictionaries. d. Production of Thai transcription The Thai phonetic transcriptions is produced automatically (with the CUTES system of Pr. Sudaporn - Chulalongkorn University) and then revised before inclusion in the dictionary database. The pronunciation of Thai is potentially ambiguous and has to be checked by hand. The CUTES tool is only available on Windows computers and would be fed with files containing extracted Thai equivalents. We first ran into problems linked to differences between Thai characters encoding on different OS. We had then to propose a safe transcription of orthographic Thai. This transcription is based on 7 bits ASCII (US-ASCII) and as such can be freely exchanged on any OS and through Internet. Consider the following dictionary entry (a more complete example is given in annex): 1 2 3 4 5 6 7 8 9 10 11abrviation /abre-vya-syon-/ n.f. abbreviation singkatan Mlle est l'abrviation de Mademoiselle Mlle is the abbreviation for Mademoiselle Mlle ialah singkatan bagi perkataan Mademoiselle Mlle!       Lines 1 and 2 are the French entry and pronunciation (in a readable form for a French reader). Line 3 is the category. Line 4 is the English equivalent. Line 5 is the Malay equivalent. Line 6 & 7 are Thai equivalents. Lines 8 to 11 are respectively the French sentence example, and equivalents in English, Malay and Thai. Transcriptions of the Thai (orthographic and phonetic) are not included here. Clearly, we could base the transcription on the field type (thai_equ, english_equ, etc.). But we have a major problem for the line 11, which mixes both Roman and Thai characters. This problem is commonly found with sentences with proper nouns, or numerals for example. One work-around is to include a tag indicating if we are in a Roman or Thai context. The tags chosen are respectively \rom. and \thai.. This is illustrated below in the line 14 (the string corresponding to the :THAI_SENTENCE_TRANSCRIBED field): 1 2 3 4 5 6 7 8 9 10 11 12 13 14:FET_ENTRY :ENTRY :FRENCH_PRON :FRENCH_CAT :ENGLISH_EQU :MALAY_EQU :THAI_EQU :THAI_EQU_TRANSCRIBED :THAI_EQU :THAI_EQU_TRANSCRIBED :FRENCH_SENTENCE :ENGLISH_SENTENCE :MALAY_SENTENCE :THAI_SENTENCE :THAI_SENTENCE_TRANSCRIBED  abrviation abre-vya-syon- n.f. abbreviation singkatan K3AMY2!1AW D4A1WY2!1AW Mlle est l'abrviation de Mademoiselle Mlle is the abbreviation for Mademoiselle Mlle ialah singkatan bagi perkataan Mademoiselle Mlle!      \rom.Mlle\thai.EHB2ZCN2K3AMY2!1AWK1AWNGK3AMW!1AHN2AHNGS4AHW e. Construction costs The global investment for the building of the FeM dictionary was of 9 man-year (108 man-month). The working experience and the data issued from this project are a good starting point for the FeT project. The estimated work for the building of the FeT dictionary is of 2 man-years for the production of Thai equivalents. But we should not forget other tasks such as: (1) the production of the Thai phonetic information by automatic transcription, (2) the checking processes, (3) the lexical database production, (4) the production of the various output formats (Microsoft Word"!, PageMaker"!, Microsoft Help"! and Alex), and (5) the production of the final version (printed and CD-ROM). All these tasks are estimated to one man-year. This delay can be kept relatively short thanks to the tools and procedures developed during the FeM project. 2. Electronic Dictionary Services Services offered by computer dictionaries go well beyond what is usually expected: more or less extended cut and paste possibilities, very beneficial logical size vs. physical size ratio (entry number vs. file size), etc. It is possible and desirable to offer services one cannot find close equivalents for unless electronically. We can already mention some of such possibilities: (1) colors and graphics, (2) hypertext links, (3) multimedia information, (4) very large amounts of information, (5) personal filtering, formatting and adaptation to user needs and desires. a. Data formatting for end users and autonomous agent We can consider all dictionary information, which is not directly linked to either the source language or the target languages: categories, cross references, glosses, labels, etc. This is what is usually called the dictionary metalanguage. It is possible to design dictionary tools and data where these information are in the native language of the reader (whatever this language is). We can thus have a French-English-Thai dictionary with glosses in English, or a French-Thai dictionary with a Thai metalanguage. In a more general way, the user can configure the dictionary tool so that that it will output the metalanguage into the language he desires irrespective of the source or target languages. To this respect, the user should be able to change these settings in a working session midcourse and to have access simultaneously to several views of the same data. We can also consider, for a monolingual dictionary (definition dictionary), the possibility to have the definition in the language of the reader irrespective of the dictionary source language (for example, French definitions of Thai words or vice-versa). All that we considered above is related to end user experiences. But we are also investigating how to make our data available to complex NLP tasks (such as Machine Translation). We are currently evaluating some DBMT (Dialog Based MT) software architectures where autonomous agents are in charge for retrieving lexical knowledge among various remote large-scale lexical databases. For such autonomous agents, explicit labeled formats are definitely more appropriate. Such formats are more verbose than what can be produced either for printed dictionary or to end users, but it is not ambiguous and easily parsable. Thus, it should include extra information such as used transcriptions, etc. In that case size restriction (which is the main constraint for printed dictionary editors) is not a primary concern. c. Generic dictionary readers: Web access The FeM dictionary is available through the Web. The main advantage compared to a local dictionary tool, is the use of a Web browser (as Internet Explorer"! or Nescape Navigator"! for instance) as a generic application widely available. Request results are generated by the dictionary server and are not pre-computed. The form presented to the user through the Web browser interface can offer (or hide) several parameters allowing one to control the formatting, the range of information detail, information level, the languages (interface, metalanguage, sources, targets), the number and nature of dictionaries looked upon, and so on. As the time this article is written there is no way to display properly at the same time French and Thai form a Web browser. This is due to the fact that Thai font do only include roman characters without diacritics with very poor results for highly diacrited languages such as French. On the other hand, the good news is that several constructors recently announced the incoming availability of support of Cascading Style Sheet (CSS1) and dynamic fonts. Basically, dynamic fonts will be downloaded to the user computer when not installed locally. These technologies should address problems related to Thai and French displayed simultaneously. b. Dedicated dictionary reader with local and remote database. It is possible to distribute lexical data under a compact and protected (by encryption) format and to made them exploitable by a reader (in the same spirit of Portable Digital Documents (PDF) and associated readers distributed by Adobe). From this point, we can consider two research and development directions. First, data are available locally (on the end-user computer) and a dictionary tool (the reader) allows one to navigate among dictionary entries. The user can open several dictionaries, create and modify personal dictionaries, copy and paste (formatted) data in other applications, etc. We actually developed such a toolFicus which format dictionary, DOP, may be encrypted, making the reverse engineering of distributed dictionaries a difficult job. Secondly, it is also possible to consider a dictionary tool, which remotely fetches data on remote bases. The user has only the dictionary tool (and not the bases) to install on his computer. It is possible to have access to a virtually unlimited number of dictionaries without cobbling the computer resources. Dictionary updates become transparent to the user. We also developed such a tool, Alex remote. Experience shows that, the functionality number and complexity should be kept reduced compared to locally based dictionary tools. This is practically due to bandwidth and server response time, which has nothing to be compared with local computation. We consider this second solution more adapted to autonomous agents dealing with no real time tasks (such a updates of local lexical database or merging of lexical information issued from multiple sources as general dictionaries, specialized terminology banks, etc.). One strong point of dedicated dictionary tools is that we can provide functionalities meaningful only for some languages, in our case: Thai. The Thai extensions provided in our Ficus prototype (as contextual menus), allow the user to display or hide the word segmentation in the orthographic Thai equivalent. We are also considering producing on the fly a Speech Synthesis of the Thai which in our case could be acceptable because error free (we already have the phonetic transcription). d. Passive and active dictionary tools The above-presented approaches mean that the user has to go and fetch the data. He has to activate the dictionary tool and key in the word to look up (at least). These tools are passive. Active tools initiate by themselves the lookup upon the monitoring of the user activity. For example, such a tool (as the Ficus prototype we implemented) will scrutinize selected words on the current application (cf. figure 8) and make the lookup. If the word candidate is found in the open dictionaries, the corresponding information is formatted and proposed to the user in a non-intrusive way. The user is then free to consider this information and to manipulate it. As the user is not solicited, this kind of approach leaves the user free to concentrate on his work. This last aspect is crucial for usability. From a technical point of view, a preprocessing (such a lemmatization, or morphological analysis) is needed before the lookup. Furthermore, the potential ambiguity (several lemmas issued from the word candidate) should be handled. For instance, in French avoir (to have) and avion (plane) pour avions (we had/planes). In English, we can find the noun book and the verb to book in the form books. Conclusion It is valuable to produce multilingual dictionaries and to be able to successfully distribute them. We consider that a low technical level approach for the building of multilingual dictionaries can be a main success factor. The systematic inclusion of English equivalents is made necessary for their building and for the sake of their quality. Production methodology should integrate computer tools mastered by lexicographers, which are essentially word processors. It is thus possible to have a precise management of project, which does not disrupt lexicographer work. Whatever, the approach taken, a dictionary project cannot be considered as a small and easy task. Beside the printed distribution, we have presented in this paper several dictionary services. Contrary to the construction task, dictionary services can be highly technical (but should remain simple to use). The typology of such services can be divided among the following criteria: local or remote database dictionary, dedicated or specific dictionary reader and tools, passive or active dictionary tools. We hope that this work will inspire new dictionary projects and make flourish such services and tools, both usable for autonomous agents and end users. References [1] Gaschler, J. and M. Lafourcade (1994) Manipulating human-oriented dictionaries with very simple tools. Proc. COLING-94, August 5-9 1994, Makoto Nagao & ICCL, vol. 1/2, pp 283-286. [2] Gut Y (1996)., R. Puteri, Z. Yusoff, C. K. Choy, S. A. Samat, Ch. Boitet, N. Nedeau, M.Lafourcade, J.Gaschler, D. Levenbach (1996) Kamus Perancis Melayu Dewan - dictionnaire franais-malais. Dewan Bahasa dan Pustaka, Kuala Lumpur, 667p [3] Lafourcade, M. and G. Srasset (1993) DOP (Dictionary Object Protocol). GETA-IMAG, Grenoble, Common Lisp Object System (MCL - CLOS), Apple Macintosh, version 2.0. [4] Unit Terjemahan Melalui Komputer (1996) Lexique de terminologie informatique franais-anglais-malais. 166p. Annexes 1 Figures abandonner /aban-done-/ v.tr. (laisser) to leave \8 CSOmSTR#MENUhmnu*S_WPNCSOpzFU STR eWSajEuCMvurlMWzo1" "" cette mre a abandonn ses enfants this mother left her children  0 "" H"x! " (dserter) (milit.) to desert  " " (renoncer ) to give up to abandon ! H" H"! H" H" " il a abandonn son projet he had gave up his project !  0 H"! H"  " "!  (cder) to give in to s'abandonner /Saban-done-/ v.pr. s'abandonner to give oneself up to   +" " +" elle s'est abandonne au dsespoir she has given up to despair ! "" +"     French entry French pronunciation category (transitive verb) gloss (first meaning) English equivalent Thai equivalent Thai equivalent French sentence example English sentence example equivalent Thai sentence example equivalent gloss (second meaning) label English equivalent Thai equivalent gloss (third meaning) English equivalent English equivalent Thai equivalent Thai equivalent Thai equivalent French sentence example English sentence example equivalent Thai sentence example equivalent gloss (fourth meaning) English equivalent Thai equivalent sub-entry (pronominal form) pronunciation category phrase English phrase equivalent Thai phrase equivalent Thai phrase equivalent French sentence example English sentence example equivalent Thai sentence example equivalent Figure 3. Entry sample of the French-English-Thai dictionary.  Figure 4. User interface of the Alex dictionary tool. The user can look for a word and navigate through the entry list. Data cannot be modified for distributed dictionaries, but only copied as a formatted text. One can filter out some fields.  Figure 5. A specific Web form for the French-English-Malay dictionary (with French interface)  Figure 6. The user can select the kind of information he needs.  Figure 7. A Web query answer for the French word aimer (like, love) with English equivalents. Here, glosses are in French, but the interface is in English.  Figure 8. A FICUS window (on the right) window behind a common word processor. The user just selects words and some dictionary lookup is automatically undertaken. The information found is then proposed to the user in a non-intrusive way. Ficus is a generic dictionary service, which can cooperate with various applications. As this tool has been developed by the author of this paper, we have control over the rendering of any entry contents. The situation is not yet as favorable with general Web browsers. Annex 2 Table of Thai characters, Mac & PC codes, minimal transcription, & pronunciation This transcription (or transliteration) has been proposed by Christian BOITET (GETA, CLIPS, IMAG - Grenoble, France) and Udom WAROTAMASIKKADIT (University Ramkhamhaeng - Bangkok). Some remarks have been added. This table includes the transcription of Thai characters but not context tags. This table is a slight adaptation of a transcription table prepared in 1986 at Grenoble. The aims of this transcription are that it should be (1) minimal, hence portable; (2) reversible to the original Thai writing; (2) relatively easy to pronounce by a French native speaker. The codes in the Mac (Mac Roman) and Windows systems have been added for practical reasons. It must be noted that only one "multiple vowel", AM, is coded as one byte. All other multiple vowels are coded as 2 or more bytes, although they should be treated as units (actually as first grade diacritics) for sorting purposes. C = Consonant, V = Vowel, T = Tone, D = (other) Diacritic. Codes are in hexadecimal notation. type CVTD#charactertranscriptioncode MacOSnameprononciationremarksC1GA1GAWG/KC2K1A2KAW KAI!C3K2A3KAW KUATC4K3A4KAW KWAIC5" K4A5KAW KOH!NobsoleteC6K5A6KAW RAH!-KAH!NGC7NGA7NGAWC8JA8JAWJ/TC9C1A9CHAWCH/TC10"!C2AACHAW CHAHNGCH/TC11S1ABSAWS/TC12C3ACCHAW CHUHvery rareC13`"Y1ADYAW YEENGY/NC14D1AEDAW CHAH!-DAHD/TC15D2AFDTAW BPAH!-DTAH!KDT/TC16"T1B0TAW TAHNC17T2B1TAW MOH!N-TOHC18d"T3B2TAW POO-TAO!C19e"N1B3NAW-NEHNC20D3B4DAW DEH!KD/TC21D4B5DTAW DTAO!DT/TC22"T4B6TAW TOO!NGC23"T5B7TAW TAH-HAHNC24"T6B8TAW TOHNGC25N2B9NAW NOOC26+"B1BABAWB/PC27B2BBBPAWBP/PC28P1BCPAWC29&!F1BDFAWF/-C30P2BEPAW PAHNC31F2BFFAW PAHN???C32P3C0PAW SAH!M-PAO!C33MC1MAWC34Y2C2YAW YAH!KY/vowelC35"RC3RAWR/NC ???C4???C36H"L1C5LAW LEE!NGL/NC "???C6???C37WC7WAWW/vowelC38S2C8SAW SAH-LAHS/TC39S3C9SAW REU-SEES/TC40S4CASAW SEUAS/TC41H1CBHAWC42L2CCLAW JOO!-LAHrareC43AWCDAWC44H2CEHAHH/-D1ZACFabbreviationV1A2D0AH!V2A1D1AH!mV3뗖UAUA!V4AHD2AHV5AMD3AH!MV6IHD4IH!V7EED5EEV8E1D6EU!V9060263B}Version2.5^^&&{91493456-5A91-11CF-8700-00AA0060263B}SlideShowWindo%E2D7EUV10U1D8OO!V11xU2D9OOD2D ZBDAseparator?V12! EHE0EHmV13!  E! EH!(12+1)mV14!  AO AO!(12+4)mV15!   A! AW!(14+1)mV16!  UH UH!(12+6)mV17!  IA IA(12+7+YAW)mV18! YAIA!(17+1)mV19EAEUA(12+8+AW)mV20ՖUAEUA!(19+1)V21A4E1AAmV22A5AA!(21+1)V23OE2OHmV24O!OH!(21+1)V25AIE3AI!V26AYE4AI!???E5???E6D3ZCE7?shorteningT1!1E8MAI-EHKlow/falling (')T2!2E9MAI-TOHhigh/falling (v)T3!3EAMAI-DTREErising? (w)T4!4EBMAI-JATTAWArising (+)D4ZDECsilencingN146}Z0F0thai digit: 0N2Z1F11N3Z2F22N4Z3F33N5Z4F44N61Z5F55N7Z6F66N8Z7F77N9Z8F88N10Z9F99 Annex 3  Extended abstract A multilingual dictionary construction project (known as FeT for French-English-Thai) is the occasion to present and analyze 1) some computing issues related to Thai languages and 2) some difficulties encountered for the dictionary construction and electronic distribution. We will not detail here the aspects concerning the printed format production and distribution. This project (started mid 1996) inherited from the results (both data and methodology) of a French-English-Malay project achieved in July 1996. In this project, we are targeting two kinds of dictionaries. The first one is a general dictionary of about 20.000 entries (around 50.000 word senses), containing information about the pronunciation (both French and Thai), the word category, the gender, some meaning refinement, some phrases and locutions (more than 11.000) and some sentence examples (more than 3.000). Novice learners (Thai and French) should be able to use this dictionary with ease and profit. The second type of dictionary is a lexicon in computer science terminology (also trilingual). It contains roughly 5.000 entries in each language, with category and pronunciation but without neither examples nor locutions. Several aspects of Thai make it difficult not only to learn but also to computerize. Word segmentation is not explicitly done and should then be indicated for learners. The marking of word boundaries is also useful for more efficient compilation and processing of computer implementation of the dictionary. We used a transcription of written Thai (an extended version to the transcription proposed by the Royal Academy), in the dictionary database from which actual Thai strings (as displayed to the end user) are computed on the fly. This orthographic transcription indicates word boundaries and also syllables (which are crucial to beginners to match the string to its pronunciation transcription). Moreover, this strategy allowed us to be independent to specific Thai characters coding and, thus, made possible 1) the dictionary development on several Operating Systems (Windows and MacOS) and 2) the presence in the same string of diacrited French and Thai characters. As sentence examples often contain (French) proper nouns, their Thai translation contains both Roman and Thai characters. The transcription should then handle a language tag indicating whether the current language is Thai or French. A second difficulty is Thai pronunciation, which makes its transcription needed to learners. This phonetic transcription should be at the same time readable and informative (tones have to be indicated). For the same reasons as mentioned above, the phonetic transcription should indicate if the current characters are French or Thai. Also, the way the pronunciation would be transcribed would differ if the reader were Thai or French (or English). We had to choose one given transcription for the dictionary construction phase, leaving to the dictionary tool the possibility to display several kinds of transcriptions according to the user. Any transcription proposed to the end user besides being readable and informative should be computer efficient. Matching all these constraints at the same seemed not feasible and storing all possible transcription was not acceptable. Thus compact (but not very readable) versions of the transcriptions are used for the electronic form, from which the different (readable) versions are generated dynamically. The first part of this paper presents the general methodology we adopted for the construction of these dictionaries. As 1) dictionary building is a complex collaborative project and 2) computer resources were scarce, we have deliberately taken a low technical level approach by not using specialized tools. We then put the emphasis on the transcriptions problems and how they were handled during the dictionary production phase (done by lexicographers) and by the distiller, the tool which produces the computer version of the dictionary. For the electronic distribution, we investigated (quite) high technical solutions, some of which may not be reasonably applicable today (but surely tomorrow). On this issue, we present different kinds of dictionary services we developed to make lexical resources accessible and exploitable to end-users. 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(+33) 04.67.41.85.71 Fax. - 85.00 email: Mathieu.Lafourcade@lirmm.frWanchai RIVEPIBOON Software Eng. Lab. Dept. of Comp. Eng. Faculty of Eng. Chulalongkorn University Bangkok 10330 Thailand Tel.(66-2) 218 6988 Fax. - 215 6955 email Wanchai.R@chula.ac.th (last revision September 1998) Abstract This paper first presents some issues in the FET project, which aims at building a French-English-Thai dictionary. This project started from the results of a previous French-English-Malay dictionary achieved in July 1996. Specificities of Thai were the origin of problems linked to writing systems, orthographic transcriptions, and phonetic transcriptions. We also explored what could be the desirable form of multilingual electronic dictionaries. Keywords Multilingual dictionaries, dictionary construction, dictionary services, tools and servers, orthographic transcription, phonetic transcription. Introduction A multilingual (known as FeT for French-English-Thai) dictionary construction project is the occasion to present and analyze some problems linked to Thai and issues for the dictionary (1) construction and (2) electronic distribution. We will not detail here the aspects concerning the printed format production and distribution. This project inherited the results (both data and methodology) of a French-English-Malay project achieved in July 1997 [2]. We are targeting two kinds of dictionaries. The first one is a general dictionary of about 20.000 entries (around 50.000 word senses), containing information about the pronunciation (both French and Thai), the word category, the gender, some meaning refinement, some phrases and locutions (more than 11.000) and some sentence examples (more than 3.000). Novice learners (Thai and French) should be able to use this dictionary with ease and profit. The second type of dictionary [4] is a lexicon in computer science terminology (also trilingual). It contains roughly 5.000 entries in each language, with category and pronunciation but without examples, nor locutions. Thai and its encoding made the transcription aspects crucial. Furthermore, we had to deal with the production of the phonetic transcription of the Thai equivalents. These transcriptions are needed for the end-user to figure out segmentation and pronunciation of Thai. They are also instrumental during the building phase of the dictionary, as we worked in a heterogeneous environment (Windows and MacOS). This paper first presents the methodology we adopted for the construction of these dictionaries. As (1) dictionary building is a complex collaborative project and (2) computer resources were scarce, we have deliberately taken a low technical level approach by not using specialized tools. 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