We present a comparative investigation of word representations for part-of-speech (POS) and morphological tagging, focusing on scenarios with considerable differences between training and test data where a robust approach is necessary. Instead of adapting the model towards a specific domain we aim to build a robust model across domains. We developed a test suite for robust tagging consisting of...

We present an algorithm for local word grouping to extricate fixed word order dependencies in Hindi sentences. Local word grouping is achieved by defining regular expressions for the word groups. Ambiguities occurring during word grouping are also resolved. Hindi being a free order language, fixed order word group extraction is essential for decreasing the load on the free word order parser. Th...

Accurate and reliable part-of-speech tagging is useful for many Natural Language Processing (NLP) tasks that form the foundation of NLP-based approaches to information retrieval and data mining. In general, large annotated corpora are necessary to achieve desired part-of-speech tagger accuracy. We show that a large annotated general-English corpus is not sufficient for building a part-of-speech...

We describe a “direct modeling” approach to using prosody in various speech technology tasks. The approach does not involve any hand-labeling or modeling of prosodic events such as pitch accents or boundary tones. Instead, prosodic features are extracted directly from the speech signal and from the output of an automatic speech recognizer. Machine learning techniques then determine a prosodic m...

Arabic is a morphologically rich language, which presents a challenge for part of speech tagging. In this paper, we compare two novel methods for POS tagging of Arabic without the use of gold standard word segmentation but with the full POS tagset of the Penn Arabic Treebank. The first approach uses complex tags that describe full words and does not require any word segmentation. The second app...

. Software requirements are usually written in natural language (NL) or speech language which is asymmetric and irregular. This paper presents a suitable method for transforming user software requirement specifications (SRS) and business designs written in natural language into useful object oriented models. Here a neoteric approach is proposed to generate object oriented items from SRS. For NL...

We explore the application of memorybased learning to morphological analysis and part-of-speech tagging of written Arabic, based on data from the Arabic Treebank. Morphological analysis – the construction of all possible analyses of isolated unvoweled wordforms – is performed as a letter-by-letter operation prediction task, where the operation encodes segmentation, part-of-speech, character cha...

We explore the application of memorybased learning to morphological analysis and part-of-speech tagging of written Arabic, based on data from the Arabic Treebank. Morphological analysis – the construction of all possible analyses of isolated unvoweled wordforms – is performed as a letter-by-letter operation prediction task, where the operation encodes segmentation, part-of-speech, character cha...

In order, to make text a suitable input to an automatic method of information extraction it is usually transformed from unstructured source of information into a structured format. Part of Speech Tagging is one of the preprocessing steps which assign one of the parts of speech to the given word. In this paper we had discussed various models of supervised and unsupervised technique shown the com...

Automatic morphosyntactic tagging of corpora is usually imperfect. Wrong or strange tagging may be automatically repeated following some patterns. It is usually hard to manually detect all these errors, as corpora may contain millions of tags. This paper presents an approach to detect sequences of part-of-speech tags that have an internal cohesiveness in corpora. Some sequences match to syntact...