IRIS - English-Irish Translation System
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1 IRIS - English-Irish Translation System Mihael Arcan, Unit for Natural Language Processing of the Insight Centre for Data Analytics at the National University of Ireland, Galway
2 Introduction about me, Natural Language Processing Unit, my study and motivation,... Statistical Machine Translation (SMT) SMT training, word/phrase alignments, ambiguity, examples, evaluation IRIS - English-Irish Translation System used resources, evaluation, future work 2
3 about me* PhD Student at Insight Centre for Data NUI Galway supervised by Dr. Paul Buitelaar studied German Language (Diploma study) at the University of Ljubljana, Slovenia Masters degree in Computational Linguistics at the Ruhr University in Bochum, Germany 3
4 Unit for Natural Language Processing 4
5 Reseach Topics in UNLP Entity Linking Expertise Mining Linguistic Linked Data Content-based Linked Data Summarisation Semantic Similarity and Relatedness Suggestion Extraction Taxonomy Construction Term Translation 5
6 Motivation of my Study Business Information query in English 6
7 Motivation of my Study Business Information query in English -> Google Translate -> 7
8 Motivation of my Study Business Information query in English -> domain aware SMT-> 8
9 Issue 1 with SMT (in Term Translation) Source text: bartonellosis (1) Reference text: bartonellose Target text (generic translation model) bartonellosis (2) bartonellosis (3) Out-of-Vocabulary (OOV) Problem Target text (domain-specific model) bartonellosis (1) ICD (International Classification of Diseases) ontology (2).../tetra_old/, general (3) Google Translate, 2.6.'15 9
10 Issue 2 with SMT (in Term Translation) Source text: cash flow hedges Reference text: Absicherungen von Zahlungsströmen Target text (generic model) Cashflow-Hedges ( ) (1) Cashflow Hecken (2) Out-of-Domain Translation Target text (domain-specific model 3 ) Absicherungen von Zahlungsströmen ( ) 1) Google Translate, 3.5.'15 (2).../tetra_old/, general ( (3) financial 10
11 Introduction Natural Language Processing Unit, about me, my study, motivation,... Statistical Machine Translation (SMT) SMT training, word/phrase alignments, ambiguity, examples, evaluation IRIS - English-Irish Translation System used resources, evaluation, future work 11
12 Models in Statistical Machine Translation Translation Model lexical correspondence between languages fixed asset anlagevermögen Language Model takes care of fluency (and lexical choice) in the target language anlagevermögen
13 Training Data (Parallel Corpora) for SMT Source document Target document 13
14 Training Data for SMT Sentence aligned parallel data sentence one with some words sentence two with more words... satz eins mit einigen wörtern satz zwei mit weiteren wörtern... 14
15 Training Data for SMT Sentence aligned parallel data Word Alignment sentence one with some words sentence two with more words... satz eins mit einigen wörtern satz zwei mit weiteren wörtern... 15
16 Word Alignment Scenarios 16
17 Word Alignment Scenarios 17
18 Word Alignment Scenarios 18
19 Word Alignment Scenarios 19
20 Word Alignment Scenarios 20
21 Word Alignment with IBM Models Models IBM Model 1 IBM Model 2 IBM Model 3 IBM Model 4 IBM Model 5 Function of the model lexical translation adds absolute reordering model adds fertility model adds relative alignment model fixes deficiency 21
22 IBM Model 1 Practical Session Training data: Source Document das Haus das Buch ein Buch Target Document the house the book a book 22
23 das haus das buch ein buch the house the book a book 23
24 das haus das buch ein buch the house the book a book e f Initial 1st iter. 2nd iter. 3rd iter.... Final the das book das house das the buch book buch a buch book ein a ein the haus house haus
25 das haus das buch ein buch the house the book a book e f Initial 1st iter. 2nd iter. 3rd iter.... Final the das book das house das the buch book buch a buch book ein a ein the haus house haus
26 das haus das buch ein buch the house the book a book e f Initial 1st iter. 2nd iter. 3rd iter.... Final the das book das house das the buch book buch a buch book ein a ein the haus house haus
27 das haus das buch ein buch the house the book a book e f Initial 1st iter. 2nd iter. 3rd iter.... Final the das book das house das the buch book buch a buch book ein a ein the haus house haus
28 das haus das buch ein buch the house the book a book e f Initial 1st iter. 2nd iter. 3rd iter.... Final the das book das house das the buch book buch a buch book ein a ein the haus house haus
29 das haus das buch ein buch the house the book a book e f Initial 1st iter. 2nd iter. 3rd iter.... Final the das book das house das the buch book buch a buch book ein a ein the haus house haus
30 das haus das buch ein buch the house the book a book Lexical (word) probabilities (after 10 iterations): buch book a the das the house book haus house the ein a book
31 das haus das buch ein buch the house the book a book Decoding (translating) using the lexical probabilities: ein buch a book 0.25 book book 0.01 das haus the house 0.25 the the 0.01 das buch the book
32 das haus das buch ein buch the house the book a book Decoding (translating) using the lexical probabilities: ein buch a book 0.25 book book 0.01 das buch the book 0.25 das haus the house 0.25 the the 0.01 ein haus a house 0.25 book house
33 Language Ambiguity in SMT Source language Target language freundliche 1 bank 2 friendly 1 bank 2 gemütliche 3 bank 4 cosy 3 bench 4 freundliche 1 friendly 1 gemütliche 5 cosy 5 schlechte 6 bad 6 schlechte 6 bank 2 bad 6 bench bad 6 bank
34 Generic Models in SMT Source language Target language freundliche 1 bank 2 friendly 1 bank 2 gemütliche 3 bank 4 cosy 3 bench 4 freundliche 1 friendly 1 gemütliche 5 cosy 5 schlechte 6 bad 6 grüne 7 bank 4 green 7 bench 4 schlechte 6 bank 2 bad 6 bench bad 6 bank
35 Domain aware Models in SMT Source language Target language freundliche 1 bank 2 friendly 1 bank 2 gemütliche 3 bank 4 cosy 3 bench 4 freundliche 1 friendly 1 gemütliche 5 cosy 5 schlechte 6 bad 6 multinationale 7 bank 2 multinational 7 bank 2 schlechte 6 bank 2 bad 6 bank bad 6 bench
36 From Word to Phrase Based SMT Maria, Mary no, did not daba una bofetada, slap a la, the bruja, witch verde, green Maria no, Mary did not no daba una bofetada, did not slap daba una bofetada a la, slap the bruja verde, green witch Maria no daba una bofetada, Mary did not slap no daba una bofetada a la, did not slap the a la bruja verde, the green witch 37
37 Generic Models in SMT Source language Target language freundliche 1 bank 2 friendly 1 bank 2 gemütliche 3 bank 4 cosy 3 bench 4 freundliche 1 friendly 1 gemütliche 5 cosy 5 schlechte 6 bad 6 grüne 7 bank 4 green 7 bench 4 freundliche 1 bank 2 friendly 1 bench friendly 1 bank
38 Generic Models in SMT Source language Target language freundliche_bank 1 friendly_bank 1 gemütliche_bank 1 cosy_bench 2 freundliche 3 friendly 3 gemütliche 4 cosy 4 schlechte 5 bad 5 grüne_bank 6 green_bench 6 freundliche_bank 1 friendly_bank
39 Why are phrases better? Prime Minister Ayrault said: "It's incredible that an allied country like the United States at this point goes as far as spying on private communications that have no strategic justification, no justification on the basis of national defence. Premierminister ayrault sagte: "es ist unglaublich, dass eine verbündete Land wie die Vereinigten Staaten an diesem Punkt geht so weit wie Spionage auf private Mitteilungen, dass keine strategische Gründe, keine Begründung auf der Grundlage der nationalen Verteidigung. " 40
40 Decoding Lexical probabilities: buch book a the haus house the das the house book ein a book
41 Decoding - Finding the best path Best translation = probability of Translation Model * Language Model 42
42 Introduction Natural Language Processing Unit, about me, my study, motivation,... Statistical Machine Translation (SMT) SMT training, word/phrase alignments, ambiguity, examples, evaluation IRIS - English-Irish Translation System used resources, evaluation, future work 43
43 IRIS English-Irish Translation System* 44
44 IRIS English-Irish Translation System* it uses Moses Translation Toolkit translates from English into Irish and Irish into English (with optional translations) Irish interface build on publically available data used in UNLP/Insight projects (Kennys Bookshop, DBpedia as Gaeilge, OTTO) alows users to add new data to the system 45
45 Resources for IRIS Resource # of lines # English words # Irish words BLEU DGT.en-ga 36, , , EUbookshop.en-ga 121,042 2,606,607 2,704, EUconst.en-ga 6, , , focal_en_ga , , , GNOME.en-ga 75, , , irish-legislation ,314 2,691,928 2,792, KDE4.en-ga 110, , , news.2007.shuffled* 3,782,548 / 90,490, Ubuntu.en-ga 191 1,038 1, wikipedia_all_enga 17,421 35,165 36, ,612 7,580,187 7,978,748 46
46 IRIS Wish List (Future Work) getting feedback on the system publications on IRIS improving translation quality using more parallel/monolingual Irish data improving translation time ignoring translation candidates with low probability, direct recasing,... evaluation of translation quality manual evaluation of machine translation 47
47 IRIS - English-Irish Translation System Mihael Arcan, UNLP, Insight@NUI Galway mihael.arcan@insight-centre.org 48
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