Carlos Henríquez

Also published as: Carlos A. Henráquez Q., Carlos A. Henríquez Q., Carlos Henriquez


2012

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The TALP-UPC phrase-based translation systems for WMT12: Morphology simplification and domain adaptation
Lluís Formiga | Carlos A. Henríquez Q. | Adolfo Hernández | José B. Mariño | Enric Monte | José A. R. Fonollosa
Proceedings of the Seventh Workshop on Statistical Machine Translation

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Proceedings of ACL 2012 Student Research Workshop
Jackie C. K. Cheung | Jun Hatori | Carlos Henriquez | Ann Irvine
Proceedings of ACL 2012 Student Research Workshop

2011

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Deriving translation units using small additional corpora
Carlos A. Henríquez Q. | José B. Mariño | Rafael E. Banchs
Proceedings of the 15th Annual conference of the European Association for Machine Translation

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Enhancing scarce-resource language translation through pivot combinations
Marta R. Costa-jussà | Carlos Henríquez | Rafael E. Banchs
Proceedings of 5th International Joint Conference on Natural Language Processing

2010

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Using Collocation Segmentation to Augment the Phrase Table
Carlos A. Henríquez Q. | Marta Ruiz Costa-jussà | Vidas Daudaravicius | Rafael E. Banchs | José B. Mariño
Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR

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UPC-BMIC-VDU system description for the IWSLT 2010: testing several collocation segmentations in a phrase-based SMT system
Carlos Henríquez | Marta R. Costa-jussà | Vidas Daudaravicius | Rafael E. Banchs | José B. Mariño
Proceedings of the 7th International Workshop on Spoken Language Translation: Evaluation Campaign

This paper describes the UPC-BMIC-VMU participation in the IWSLT 2010 evaluation campaign. The SMT system is a standard phrase-based enriched with novel segmentations. These novel segmentations are computed using statistical measures such as Log-likelihood, T-score, Chi-squared, Dice, Mutual Information or Gravity-Counts. The analysis of translation results allows to divide measures into three groups. First, Log-likelihood, Chi-squared and T-score tend to combine high frequency words and collocation segments are very short. They improve the SMT system by adding new translation units. Second, Mutual Information and Dice tend to combine low frequency words and collocation segments are short. They improve the SMT system by smoothing the translation units. And third, GravityCounts tends to combine high and low frequency words and collocation segments are long. However, in this case, the SMT system is not improved. Thus, the road-map for translation system improvement is to introduce new phrases with either low frequency or high frequency words. It is hard to introduce new phrases with low and high frequency words in order to improve translation quality. Experimental results are reported in the French-to-English IWSLT 2010 evaluation where our system was ranked 3rd out of nine systems.

2009

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The TALP-UPC Phrase-Based Translation System for EACL-WMT 2009
José A. R. Fonollosa | Maxim Khalilov | Marta R. Costa-jussà | José B. Mariño | Carlos A. Henráquez Q. | Adolfo Hernández H. | Rafael E. Banchs
Proceedings of the Fourth Workshop on Statistical Machine Translation

2008

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The TALP-UPC Ngram-Based Statistical Machine Translation System for ACL-WMT 2008
Maxim Khalilov | Adolfo Hernández H. | Marta R. Costa-jussà | Josep M. Crego | Carlos A. Henríquez Q. | Patrik Lambert | José A. R. Fonollosa | José B. Mariño | Rafael E. Banchs
Proceedings of the Third Workshop on Statistical Machine Translation