TALP Phrase-Based System and TALP System Combination for the IWSLT 2006 IWSLT 2006, Kyoto
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1 TALP Phrase-Based System and TALP System Combination for the IWSLT 2006 IWSLT 2006, Kyoto Marta R. Costa-jussà, Josep M. Crego, Adrià de Gispert, Patrik Lambert, Maxim Khalilov, José A.R. Fonollosa, José B. Mariño and Rafael Banchs Universitat Politècnica de Catalunya (UPC), Barcelona, Spain November 2006
2 1 Introduction 2 TALP-phrase system Baseline system Statistical Machine Reordering (SMR) SMR Translation Model SMR Tuple Extraction 3 Phrase-Based and N-gram-Based Combination 4 IWSLT 2006 Evaluation 5 Conclusions
3 Participation in the IWSLT 2006 Evaluation Tasks 1 Arabic to English 2 Chinese to English 3 Italian to English 4 Japanese to English Systems 1 TALP-phrase 2 TALP-comb
4 Alignment and Phrase Extraction Alignment: IBM MODEL 4 (GIZA++ (OCH, 2000)) 50 CLASSES USING MKCLS LOWER-CASED TEXT UNION Phrase Extraction: PHRASE-EXTRACTION (OCH AND NEY, 2004) NO LENGTH LIMIT
5 Log-linear combination of feature functions { M } ẽ = argmax e m=1 λ m h m (e, f ) (1) Conditional and posterior probability Target Language Model (4-grams, SRILM (Stolcke, 2002)) Forward and backward lexicon models Word bonus Phrase bonus
6 Log-linear combination of feature functions { M } ẽ = argmax e m=1 λ m h m (e, f ) (1) Conditional and posterior probability Target Language Model (4-grams, SRILM (Stolcke, 2002)) Forward and backward lexicon models Word bonus Phrase bonus Additionally, the decoder allows for non-monotonic search, taking into account two limits: distortion limit m (maximum distance measured in words that a phrase is allowed to be reordered, ) reordering limit j (maximum number of reordering jumps)
7 Statistical Machine Reordering (SMR) SMR is applied before SMT. SMR uses an SMT system to deal with reordering. SMR translates from an original source language (S) to a reordered source language (S ), given a target language (T ). In monotonized task S T, training (word alignment) is easier, and also translation (less reordering problems)
8 SMR Block Diagram
9 SMR Block Diagram
10 SMR Block Diagram
11 SMR Block Diagram
12 SMR Translation Model Building the SMR translation model...
13 SMR Translation Model Building the SMR translation model...
14 SMR Translation Model Building the SMR translation model...
15 SMR Tuple Extraction
16 SMR Translation Model Building the SMR translation model
17 TALP-comb Given the 1best outputs of each system, we perform a log-linear combination, which is computed by using the following models: IBM Model 1 for the sentence in the source to target direction. IBM Model 1 for the sentence in the target to source direction. Target language models: 2gram, 3gram and 5gram. Word bonus. And we optimize the weights of each model with the simplex algorithm.
18 Results Results for the TALP-phrase in all the tasks of the IWSLT Results for case-insensitive evaluations and without punctuation marks Two TALP-phrase systems: using SMR technique or not. In all tasks, except for the Italian to English, we used a non-monotonic search (with m = 5 and j = 3).
19 Results Results for the TALP-phrase in all the tasks of the IWSLT Results for case-insensitive evaluations and without punctuation marks Two TALP-phrase systems: using SMR technique or not. In all tasks, except for the Italian to English, we used a non-monotonic search (with m = 5 and j = 3). Task System Dev Test Eval BLEU NIST BLEU NIST BLEU NIST zh2en TALP-phrase p (SMR) TALP-phrase c
20 Results Results for the TALP-phrase in all the tasks of the IWSLT Results for case-insensitive evaluations and without punctuation marks Two TALP-phrase systems: using SMR technique or not. In all tasks, except for the Italian to English, we used a non-monotonic search (with m = 5 and j = 3). Task System Dev Test Eval BLEU NIST BLEU NIST BLEU NIST zh2en TALP-phrase p (SMR) TALP-phrase c ar2en TALP-phrase p (SMR) TALP-phrase c
21 Results Results for the TALP-phrase in all the tasks of the IWSLT Results for case-insensitive evaluations and without punctuation marks Two TALP-phrase systems: using SMR technique or not. In all tasks, except for the Italian to English, we used a non-monotonic search (with m = 5 and j = 3). Task System Dev Test Eval BLEU NIST BLEU NIST BLEU NIST zh2en TALP-phrase p (SMR) TALP-phrase c ar2en TALP-phrase p (SMR) TALP-phrase c it2en TALP-phrase p TALP-phrase c1 (SMR)
22 Results Results for the TALP-phrase in all the tasks of the IWSLT Results for case-insensitive evaluations and without punctuation marks Two TALP-phrase systems: using SMR technique or not. In all tasks, except for the Italian to English, we used a non-monotonic search (with m = 5 and j = 3). Task System Dev Test Eval BLEU NIST BLEU NIST BLEU NIST zh2en TALP-phrase p (SMR) TALP-phrase c ar2en TALP-phrase p (SMR) TALP-phrase c it2en TALP-phrase p TALP-phrase c1 (SMR) jp2en TALP-phrase p (SMR) TALP-phrase c
23 TALP Phrase-based System The SMR improved the results in the internal test. In the final evaluation, these conclusions can not be generalized, which might be explained by the high number of unknown words in the eval set Set Chinese Arabic Italian Japanese development test evaluation Table: Number of unknown words in development, test and evaluation sets.
24 Results Results for the TALP-phrase, TALP-tuple and the combination of both in all the tasks of the IWSLT (case-insensitive and without punctuations marks) Task System Dev Eval BLEU NIST BLEU NIST zh2en TALP-phrase p (SMR) TALP-phrase c TALP-tuple p TALP-tuple c TALP-comb
25 Results Results for the TALP-phrase, TALP-tuple and the combination of both in all the tasks of the IWSLT (case-insensitive and without punctuations marks) Task System Dev Eval BLEU NIST BLEU NIST zh2en TALP-phrase p (SMR) TALP-phrase c TALP-tuple p TALP-tuple c TALP-comb ar2en TALP-phrase p (SMR) TALP-phrase c TALP-tuple p TALP-tuple c TALP-tuple c TALP-tuple c TALP-comb
26 Results Results for the TALP-phrase, TALP-tuple and the combination of both in all the tasks of the IWSLT (case-insensitive and without punctuations marks) Task System Dev Eval it2en TALP-phrase p TALP-phrase c1 (SMR) TALP-tuple p TALP-tuple c TALP-tuple c TALP-tuple c TALP-comb
27 Results Results for the TALP-phrase, TALP-tuple and the combination of both in all the tasks of the IWSLT (case-insensitive and without punctuations marks) Task System Dev Eval it2en TALP-phrase p TALP-phrase c1 (SMR) TALP-tuple p TALP-tuple c TALP-tuple c TALP-tuple c TALP-comb jp2en TALP-phrase p (SMR) TALP-phrase c TALP-tuple p TALP-tuple c TALP-comb
28 TALP System Combination In the combination, we observe a general improvement of the BLEU score, whereas the NIST score seems to decrease. It can be explained by the particular features used: shorter outputs benefit both from IBM model 1 and language model, while the word bonus is not enough to compensate this.
29 Conclusions We have presented the TALP-phrase and TALP-comb systems for IWSLT 2006 evaluation. The SMR reordering technique was expected to improve translation quality in the evaluation set as it did in the internal test set. The failure of doing so may be explained by the increased number of unknown words in the evaluation set compared to the test set. We are currently studying ways to cope with unknown words in the SMR technique. The very basic combination of TALP-phrase and TALP-tuple systems succeeded in improving BLEU score, but not NIST score. Nevertheless, it is an encouragement to investigate more elaborate ways to perform the combination.
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