Baigiamajame magistro darbe nagrinėjamos automatinės vertimo sistemos, pagrindiniai jų veikimo principai ir šių sistemų integracijos būdai. Detaliai aprašoma populiarių šiuo metu statistinių vertimo sistemų struktūra, pateikiami šių ir tradicinių (taisyklėmis paremtų) sistemų privalumai ir trūkumai. Pristatomos visos šiuo metu egzistuojančios automatinio vertimo sistemos lietuvių ir anglų kalbų porai, išaiškinami jų privalumai ir trūkumai. Lingvistiniu požiūriu nagrinėjamos lietuvių ir anglų kalbos, išvardinami šių kalbų panašumai, skirtumai ir sunkumai, kylantys verčiant iš vienos kalbos į kitą. Taip pat pateikiami įvairūs automatinio vertimo įvertinimo būdai, įskaitant populiarų BLEU įvertinimo metodą. Išvardinamos ir analizuojamos užsienio autorių siūlomos automatinio vertimo sistemų integracijos architektūros. Apžvelgiami sumaišymo tinklai, kurie naudojami kuriant integruotą vertimo sistemą. Pateikiama originali mišriosios vertimo sistemos įgyvendinimo metodika. Integruota sistema yra praktiškai įgyvendinama. Šios sistemos ir kitų vertimo sistemų anglų ir lietuvių kalbų porai rezultatai yra įvertinami ir palyginami. Atlikus teorinę automatinio vertimo sistemų apžvalgą ir praktiškai įgyvendinus mišriąją vertimo sistemą, pateikiamos baigiamojo darbo išvados ir siūlymai. Darbą sudaro 6 dalys: įvadas, automatinio vertimo sistemų analizė, mišriųjų automatinio vertimo sistemų analizė, mišriosios automatinio vertimo sistemos sukūrimas, išvados, literatūros sąrašas. Darbo apimtis... [toliau žr. visą tekstą] / The Master’s thesis analyses machine translation systems, their principles of operation and the methods used in integrating these systems. The structure of popular statistical machine translation systems, as well as the advantages and disadvantages of such systems is described in detali. The existing machine translation systems for the Lithuanian-English language pair along with their abilities and shortcomings are presented. Lithuanian and English languages are analysed from the linguistic perspective. The similarities and differences between these languages, as well as the difficulties, arising in translating the text from one language to another are discussed. Moreover, different machine translation evaluation methods, including the popular BLEU metric, are reviewed. Various architectures for integrating multiple machine translation systems, offered by foreign authors, are presented and analysed. Confusion networks, which are used in integrating machine translation systems, are discussed. An original method of implementing the hybrid machine translation system is offered. The hybrid system is implemented in practice. The translation results obtained from the created system and the existing systems for the Lithuanian-English language pair are assessed and compared. Finally, after performing the theoretical review of machine translation systems and implementing the hybrid system, conclusions and recommendations are provided. The thesis consists of 6 parts: introduction, the... [to full text]

The Swedish National Board of Health and Welfare has been overseeing translations of the international clinical terminology SNOMED CT from English to Swedish. This study was performed to find whether semi-automatic methods of translation could produce a satisfactory translation while requiring fewer resources than manual translation. Using the medical English-Swedish dictionary TermColl translations of select subsets of SNOMED CT were produced by ways of translation memory and statistical translation. The resulting translations were evaluated via BLEU score using translations provided by the Swedish National Board of Health and Welfare as reference before being compared with each other. The results showed a strong advantage for statistical translation over use of a translation memory; however, overall translation results were far from satisfactory. / Den internationella kliniska terminologin SNOMED CT har översatts från engelska till svenska under ansvar av Socialstyrelsen. Den här studien utfördes för att påvisa om semiautomatiska översättningsmetoder skulle kunna utföra tillräckligt bra översättning med färre resurser än manuell översättning. Den engelsk-svenska medicinska ordlistan TermColl användes som bas för översättning av delmängder av SNOMED CT via översättnings­minne och genom statistisk översättning. Med Socialstyrelsens översättningar som referens poängsattes the semiautomatiska översättningarna via BLEU. Resultaten visade att statistisk översättning gav ett betydligt bättre resultat än översättning med översättningsminne, men över lag var resultaten alltför dåliga för att semiautomatisk översättning skulle kunna rekommenderas i detta fall.

La traduction statistique vise l’automatisation de la traduction par le biais de modèles statistiques. Dans ce travail, nous relevons un des grands défis du domaine : la recherche (Brown et al., 1993). Les systèmes de traduction statistique de référence, tel Moses (Koehn et al., 2007), effectuent généralement la recherche en explorant l’espace des préfixes par programmation dynamique, une solution coûteuse sur le plan computationnel pour ce problème potentiellement NP-complet (Knight, 1999). Nous postulons qu’une approche par recherche locale (Langlais et al., 2007) peut mener à des solutions tout aussi intéressantes en un temps et un espace mémoire beaucoup moins importants (Russell et Norvig, 2010). De plus, ce type de recherche facilite l’incorporation de modèles globaux qui nécessitent des traductions complètes et permet d’effectuer des modifications sur ces dernières de manière non-continue, deux tâches ardues lors de l’exploration de l’espace des préfixes. Nos expériences nous révèlent que la recherche locale en traduction statistique est une approche viable, s’inscrivant dans l’état de l’art. / Statistical machine translation is a concerted effort towards the automation of the translation process. In the work presented here, we explore one of the major challenges of statistical machine translation: the search step (Brown et al., 1993). State of the art systems such as Moses (Koehn et al., 2007) search by exploring the prefix search space, a computationally costly solution to this potentially NP-complete problem (Knight, 1999). We propose that a local search approach can yield solutions which are qualitatively just as interesting, while keeping memory space and execution time at lower levels (Russell et Norvig, 2010). Furthermore, this type of search facilitates the use of global models for which a complete translation is needed and allows for non-continuous modifications, two tasks made difficult by exploring the prefix search space. The experiments we have conducted reveal that the use of local search during the search step in statistical machine translation is a viable, state of the art approach.

La traduction statistique vise l’automatisation de la traduction par le biais de modèles statistiques. Dans ce travail, nous relevons un des grands défis du domaine : la recherche (Brown et al., 1993). Les systèmes de traduction statistique de référence, tel Moses (Koehn et al., 2007), effectuent généralement la recherche en explorant l’espace des préfixes par programmation dynamique, une solution coûteuse sur le plan computationnel pour ce problème potentiellement NP-complet (Knight, 1999). Nous postulons qu’une approche par recherche locale (Langlais et al., 2007) peut mener à des solutions tout aussi intéressantes en un temps et un espace mémoire beaucoup moins importants (Russell et Norvig, 2010). De plus, ce type de recherche facilite l’incorporation de modèles globaux qui nécessitent des traductions complètes et permet d’effectuer des modifications sur ces dernières de manière non-continue, deux tâches ardues lors de l’exploration de l’espace des préfixes. Nos expériences nous révèlent que la recherche locale en traduction statistique est une approche viable, s’inscrivant dans l’état de l’art. / Statistical machine translation is a concerted effort towards the automation of the translation process. In the work presented here, we explore one of the major challenges of statistical machine translation: the search step (Brown et al., 1993). State of the art systems such as Moses (Koehn et al., 2007) search by exploring the prefix search space, a computationally costly solution to this potentially NP-complete problem (Knight, 1999). We propose that a local search approach can yield solutions which are qualitatively just as interesting, while keeping memory space and execution time at lower levels (Russell et Norvig, 2010). Furthermore, this type of search facilitates the use of global models for which a complete translation is needed and allows for non-continuous modifications, two tasks made difficult by exploring the prefix search space. The experiments we have conducted reveal that the use of local search during the search step in statistical machine translation is a viable, state of the art approach.