Unsupervised dependency parsing frequently assume that input sentences have already been labeled with POS tags. Likewise, most unsupervised POS taggers (including those proposed by [1] and [2]) either produce numeric labels on words without providing a mapping to POS tags or they rely on language specific lexical information such as lists reporting the possible tags that some or all of the word...

One of the goals of text-to-speech (TTS) systems is to produce natural-sounding synthesised speech. Towards this end various natural language processing (NLP) tasks are performed to model the prosodic aspects of the TTS voice. One of the fundamental NLP tasks being used is the part-of-speech (POS) tagging of the words in the text. This paper investigates the effects of POS information on the na...

This paper presents the adaptation of the Hidden Markov Models-based TTL partof-speech tagger to the biomedical domain. TTL is a text processing platform that performs sentence splitting, tokenization, POS tagging, chunking and Named Entity Recognition (NER) for a number of languages, including Romanian. The POS tagging accuracy obtained by the TTL POS tagger exceeds 97% when TTL’s baseline mod...

Project AMALGAM explored a range of Partof-Speech tagsets and phrase structure parsing schemes used in modern English corpus-based research. The PoS-tagging schemes and parsing schemes include some which have been used for hand annotation of corpora or manual postediting of automatic taggers or parsers; and others which are unedited output of a parsing program. Project deliverables include: a d...

We develop an approach to utilize anisotropic metamaterials to solve one of the fundamental problems of modern plasmonics--parasitic scattering of surface waves into free-space modes, opening the road to truly two-dimensional plasmonic optics. We illustrate the developed formalism on the examples of plasmonic refractor and plasmonic crystal, and discuss limitations of the developed technique an...

Background: Nurses’ work engagement is essential both for the quality of service provided and occupational health. However, there a lack adequate information about nurses’ in healthcare organizations that are affected by various factors context Health Psychology.Purpose: This study was aimed at investigating association between leadership styles supervisors engagement, elucidating role organiza...

Generative latent-variable models are important for natural language processing due to their capability of providing compact representations of data. As conventional maximum likelihood estimation (MLE) is prone to focus on explaining irrelevant but common correlations in data, we apply maximum reconstruction estimation (MRE) to learning generative latent-variable models alternatively, which aim...

This paper provides a systematic approach for determining the best of three emerging network technologies – RPR, POS and GE for any given network with a set of basic network requirements. This approach uses an extensive set of evaluation criteria including raw experimental data, a realistic pricing model, scores and weights. All experimental results presented in this paper come from actual test...