A Software Tool for Semi-Automatic Part-of-Speech Tagging and Sentence Accentuation in Serbian Language
نویسندگان
چکیده
This paper presents a software tool for semi-automatic part-of-speech tagging, annotation of morphological categories and accentuation of texts in Serbian language. The software tool described in this paper is used for very efficient development of tagged text corpora in Serbian language since the accuracy of automatic POS tag and morphological category assignment is 87,2%. This result was obtained by testing the algorithm on a text containing 36692 words, and has turned out to be highly dependent on the type of text. The same algorithm for automatic POS tag and morphological category assignment can be included in text-to-speech systems, enabling correct accentuation of sentences, which, in turn, leads to fairly natural prosody. Within the test mentioned above, accent type and position were determined for each word based on automatically assigned POS tag, morphology-related information, as well as certain syntax cues, and correct accentuation assignment rate of 97,2% was achieved. Programsko orodje za polavtomatsko oblikoskladenjsko označevanje in pripisovanje stavčnega poudarka v srbskem jeziku V članku je prestavljeno programje za polavtomatsko oblikoskladenjsko označevanje, pripisovanje oblikoslovnih kategorij in mesta naglasa/poudarka besedilom v srbskem jeziku. V članku predstavljeno programsko orodje je uporabljeno za zelo učinkovit razvoj označenih besedilnih korpusov srbskega jezika; natančnost pripisovanja oblikoskladenjskih oznak je namreč okrog 88 %. Rezultat je bil dosežen s preizkušanjem algoritma na besedilnem korpusu velikosti 36.692 besed, izkazal pa se je za v veliki meri odvisnega od tipa besedil. Isti algoritem za avtomatsko oblikoskladenjsko označevanje je lahko vključen tudi v sisteme pretvorbe zapisanega v govorjeno besedilo, saj omogoča pravilen pripis stavčnega poudarka, ki vodi k precej naravni prozodiji. V zgoraj omenjenem preizkusu je bila na osnovi avtomatično pripisanih oblikoskladenjskih oznak pri ugotavljanju naglasnega tipa in mesta naglasa pri posamezni besedi dosežena natančnost 97,2 %.
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