The task of analyzing sentiment has been extensively researched for a variety languages. However, due to dearth readily available Natural Language Processing methods, Urdu analysis still necessitates additional study by academics. When it comes text processing, lot offer because its rich morphological structure. most difficult aspect is determining the optimal classifier. Several studies have i...

The students at Matric level commit certain errors in English writing. This research was conducted to find out the committed by metric Tehsil Rustam. A total of 60 – top 20 were selected from three schools They given task write on topics namely “My school”, best friend” and favourite teacher”. To analyze students, researcher applied “Darus et al model Error analysis theory”. categorized put int...

In Computational Linguistics, Hindi and Urdu are not viewed as a monolithic entity and have received separate attention with respect to their text processing. From part-of-speech tagging to machine translation, models are separately trained for both Hindi and Urdu despite the fact that they represent the same language. The reasons mainly are their divergent literary vocabularies and separate or...

There has been a great deal of research on kinship in translation and linguistics. Linguoculturologically, etymologically, it studied relation to the words reference. This article is also about related their translations into Urdu. It describes methods used by Pakistani translator translating these words, advantages disadvantages translation. In this article, more as unit

Statistical morph analyzers have proved to be highly accurate while being comparatively easier to maintain than rule based approaches. Our morph analyzer (SMA++) is an improvement over the statistical morph analyzer (SMA) described in Malladi and Mannem (2013). SMA++ predicts the gender, number, person, case (GNPC) and the lemma (L) of a given token. We modified the SMA in Malladi and Mannem (2...

The availability of valid and reliable tool to assess turnover intent in any organization is essential. This study aimed translate intention scale Urdu for employees working diverse organizations (universities, banks, hospitals). For this purpose, forward backward translation methods were adopted. After determining cross language validation, factor validity was confirmed through Confirmatory an...

This paper investigates use of a machine learnt model for recognition of individually words spoken in Urdu language. Speech samples from many different speakers were utilized for modeling. Original time-domain samples are normalized and pre-processed by applying discrete Fourier transformation for speech feature extraction. In frequency domain, high degree of correlation was found for the same ...

In Pakistan, people can often speak three languages (Urdu, English, and a regional language). The de jure policy of the country encourages vernacular languages, but facto use English Urdu. No attention is paid towards especially Punjabi. Elite schools serve as instruments for promotion English. For this reason, Urdu Punjabi are ignored by these schools. Consequently, young generation no more in...