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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

1. Turkish and Its Challenges for Language and Speech Processing

verfasst von : Kemal Oflazer, Murat Saraçlar

Erschienen in: Turkish Natural Language Processing

Verlag: Springer International Publishing

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Abstract

We present a short survey and exposition of some of the important aspects of Turkish that have proved to be interesting and challenging for natural language and speech processing. Most of the challenges stem from the complex morphology of Turkish and how morphology interacts with syntax. Finally we provide a short overview of the major tools and resources developed for Turkish over the last two decades. (Parts of this chapter were previously published as Oflazer (Lang Resour Eval 48(4):639–653, 2014).)

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Nächstes Kapitel Morphological Processing for Turkish
Fußnoten
1
These numbers were counted by using the xfst, the Xerox finite state tool (Beesley and Karttunen 2003), by filtering through composition by restricting output by the respective root words and with the number of symbols marking a derivational morpheme, and then counting the number of possible words.
 
2
See Wickwire (1987) for an interesting take on this.
 
3
It turns out that there are a couple of suffixes that can at least theoretically be used iteratively. The causative morpheme is one such morpheme, but in practice up to three could be used and even then it is hard to track who is doing what to whom.
 
4
One constraint usually mentioned is that indefinite (and nominative marked) direct objects move with the verb, but there are valid violations of that observed in speech (Sarah Kennelly, personal communication).
 
5
Although we have written out the root word explicitly here, whenever convenient we will assume that the root word is part of the first inflectional group.
 
6
uzak is far/distant; the morphological features other than the obvious part-of-speech features are: +Become: become verb, +Caus: causative verb, +Pass: passive verb, +Pos: Positive Polarity, +FutPart: Derived future participle, +Pnon: no possessive agreement.
 
7
Here we show surface dependency relations, but going from the dependent to the head.
 
8
The pre-trained MaltParser model and configuration files for Turkish can be downloaded from https://​web.​itu.​edu.​tr/​gulsenc/​TurkishDepModel.​html (Accessed Sept. 14, 2017).
 
9
See also ParGram/ParSem. An international collaboration on LFG-based grammar and semantics development: https://​pargram.​b.​uib.​no (Accessed Sept. 14, 2017).
 
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Metadaten
Titel
Turkish and Its Challenges for Language and Speech Processing
verfasst von
Kemal Oflazer
Murat Saraçlar
Copyright-Jahr
2018
Buch
Turkish Natural Language Processing

Print ISBN: 978-3-319-90163-3

Electronic ISBN: 978-3-319-90165-7

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-90165-7_1

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