5 years 7 months ago
Selective Sharing for Multilingual Dependency Parsing
We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation i...
Tahira Naseem, Regina Barzilay, Amir Globerson
6 years 9 months ago
Joint Bilingual Sentiment Classification with Unlabeled Parallel Corpora
Most previous work on multilingual sentiment analysis has focused on methods to adapt sentiment resources from resource-rich languages to resource-poor languages. We present a nov...
Bin Lu, Chenhao Tan, Claire Cardie, Benjamin K. Ts...
6 years 9 months ago
A Discriminative Model for Joint Morphological Disambiguation and Dependency Parsing
Most previous studies of morphological disambiguation and dependency parsing have been pursued independently. Morphological taggers operate on n-grams and do not take into account...
John Lee, Jason Naradowsky, David A. Smith
7 years 14 days ago
Verbs are where all the action lies: Experiences of Shallow Parsing of a Morphologically Rich Language
Verb suffixes and verb complexes of morphologically rich languages carry a lot of information. We show that this information if harnessed for the task of shallow parsing can lead ...
Harshada Gune, Mugdha Bapat, Mitesh M. Khapra, Pus...
7 years 3 months ago
Tackling Sparse Data Issue in Machine Translation Evaluation
We illustrate and explain problems of n-grams-based machine translation (MT) metrics (e.g. BLEU) when applied to morphologically rich languages such as Czech. A novel metric SemPO...
Ondrej Bojar, Kamil Kos, David Marecek
7 years 6 months ago
Morphological Richness Offsets Resource Demand - Experiences in Constructing a POS Tagger for Hindi
In this paper we report our work on building a POS tagger for a morphologically rich language- Hindi. The theme of the research is to vindicate the stand that- if morphology is st...
Smriti Singh, Kuhoo Gupta, Manish Shrivastava, Pus...
7 years 7 months ago
Enriching Morphologically Poor Languages for Statistical Machine Translation
We address the problem of translating from morphologically poor to morphologically rich languages by adding per-word linguistic information to the source language. We use the synt...
Eleftherios Avramidis, Philipp Koehn