Subject informational status and word order: Catalan as an SVO language

Forcadell, Montserrat

doi:10.1016/j.pragma.2013.03.017

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…Word order Reference Sinhala (SI) SOV (Reynolds, 1980) Bengali (BN) SOV (Bhattacharja, 2007) SVO (Forcadell, 2013) Table 5: References used to obtain word order for each language.…”

Section: Target Languagementioning

confidence: 99%

Can Lexical Semantics Improve Translation In Low-resource And Endangered Languages?

Subramanian¹,

Sundararaman

2023

Preprint

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Low-resource, especially endangered languages are often overlooked in a majority of NLP tasks. For instance, in neural machine translation (NMT), the aim is to map text from one language into another. Although many advances have been made in developing NMT systems for natural language, little research has been done on understanding how the word ordering and lexical similarity between the source and target language affect translation performance. Specifically, in the case of low-resource and endangered languages, translation performance can often be enhanced through model architectures that leverage this understanding. Here, we investigate these relationships on a variety of low-resource, endangered Eurasiatic language pairs from the OpenSubtitles2016 database, where the source language is English, and find that the more similar the target language is to English, the greater the translation performance. In addition, we study the impact of providing NMT models with part of speech (POS) of words in the English sequence and find that, for Transformer-based models, the more dissimilar the target language is from English, the greater the benefit provided by POS. Our findings could further enhance interdisciplinary collaboration to develop NLP models to benefit speakers of many endangered languages

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“…Word order Reference Sinhala (SI) SOV (Reynolds, 1980) Bengali (BN) SOV (Bhattacharja, 2007) SVO (Forcadell, 2013) Table 5: References used to obtain word order for each language.…”

Section: Target Languagementioning

confidence: 99%

Can Lexical Semantics Improve Translation In Low-resource And Endangered Languages?

Subramanian¹,

Sundararaman

2023

Preprint

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“…LSC, an SVO language (Forcadell 2013), provides a novel signed RC marker that has not been reported for other SLs (Mosella Sanz 2011). This is the sign mateix 'the same', which has apparently been grammaticalized into a nominalizer, and can be used outside of RCs in constructions like red mateix 'the red one' or poss-1 mateix 'mine'.…”

Section: Catalan Sign Language (Lsc)mentioning

confidence: 99%

Internally-headed relative clauses in sign languages

Wilbur

2017

Volume 2

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This chapter considers relative clause data from sign languages in light of their variation with respect to basic word order, nonmanual marking, and presence/absence of internally-headed and externally-headed relative clauses. Syntactically, a double merge cartographic model (Cinque 2005a;, following Brunelli (2011), is adopted. The differences across sign languages are suggested to result from differences in raising requirements with respect to the relative clauses themselves and with respect to their heads, rather than basic word order, use of complementizers, relative pronouns, or nominalizers, or (type of) nonmanual marking. Typologically, it is noted that several of the SVO SLs have IHRCs, that at least one SOV SL does not have IHRCs, and that three of the SLs have both internally-headed (IHRCs) and externally-headed (EHRCs) relative clauses.

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“…In Catalan, for instance, interrogative sentences, must present subjects in a right-dislocated slot (Forcadell 2007, 199-219). Likewise, postverbal subjects, unless they are narrow-focus or in sentences with very specific verb types (e.g., unaccusatives) will also be necessarily right-dislocated (Forcadell 2013b). These internal language constraints will have an effect on the number of dislocations that the Catalan texts will naturally present.…”

Section: Dislocated Structures In the Translated Textsmentioning

confidence: 99%

The translation into Catalan of marked structures inKing Lear

Guinjoan

2014

Zeitschrift Für Romanische Philologie

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Different languages have different means (or structures) to either foreground or background the informational (thematic-rhematic) import of the constituents involved in their sentences. English and Catalan differ substantially, since these two languages resort to two different types of strategies to encode such pragmatic information. Whereas in English thematic (old) information may be left deaccented inside the clause, in Catalan it must be moved to a peripheral (dislocated) position in the structure. This might trigger the binding of a clitic in the clause to satisfy the requirements of the verb. Hence, in order to maintain the quality of the original text, translators should be aware of the equivalences that marked structures have in the target language so as to avoid the weakening of the quality of the target text. If the choice of marked structures is relevant in the original text, that choice should be reflected in (quality) target texts as well. To approach how marked structures are treated in translations, four strategies (which are either contrastive and/or involve clitic binding in Catalan) will be analysed in a fragment of Shakespeare's King Lear.

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Subject informational status and word order: Catalan as an SVO language

Cited by 5 publications

References 12 publications

Can Lexical Semantics Improve Translation In Low-resource And Endangered Languages?

Can Lexical Semantics Improve Translation In Low-resource And Endangered Languages?

Internally-headed relative clauses in sign languages

The translation into Catalan of marked structures inKing Lear

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