12,819 research outputs found
The emergence of prosody in linguistic theory
Prosody is a unique character in the production of sounds. Human speech is particularly marked by prosody for various functions in the different aspects of linguistics (e.g. phonology, morphology, sociolinguistics). The importance of prosody in human language had been known since very early periods of modern civilisation. Both Western and Eastern traditions had put a lot of emphasis on the proper practice of prosodic rhymes and rhythms in the use of language whether it was for analysing grammar or for praying to God or any other superior spirit. Subsequent developments in linguistics have revealed the central role played by prosody in determining the innate grammar of human language. This paper attempts to discuss in brief the evolution of the thought on prosody and its current standing in the field of linguistics.peer-reviewe
ON MONITORING LANGUAGE CHANGE WITH THE SUPPORT OF CORPUS PROCESSING
One of the fundamental characteristics of language is that it can change over time. One
method to monitor the change is by observing its corpora: a structured language
documentation. Recent development in technology, especially in the field of Natural
Language Processing allows robust linguistic processing, which support the description of
diverse historical changes of the corpora. The interference of human linguist is inevitable as
it determines the gold standard, but computer assistance provides considerable support by
incorporating computational approach in exploring the corpora, especially historical
corpora. This paper proposes a model for corpus development, where corpus are annotated
to support further computational operations such as lexicogrammatical pattern matching,
automatic retrieval and extraction. The corpus processing operations are performed by local
grammar based corpus processing software on a contemporary Indonesian corpus. This
paper concludes that data collection and data processing in a corpus are equally crucial
importance to monitor language change, and none can be set aside
Embedding Web-based Statistical Translation Models in Cross-Language Information Retrieval
Although more and more language pairs are covered by machine translation
services, there are still many pairs that lack translation resources.
Cross-language information retrieval (CLIR) is an application which needs
translation functionality of a relatively low level of sophistication since
current models for information retrieval (IR) are still based on a
bag-of-words. The Web provides a vast resource for the automatic construction
of parallel corpora which can be used to train statistical translation models
automatically. The resulting translation models can be embedded in several ways
in a retrieval model. In this paper, we will investigate the problem of
automatically mining parallel texts from the Web and different ways of
integrating the translation models within the retrieval process. Our
experiments on standard test collections for CLIR show that the Web-based
translation models can surpass commercial MT systems in CLIR tasks. These
results open the perspective of constructing a fully automatic query
translation device for CLIR at a very low cost.Comment: 37 page
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