Towards Transliteration between Sindhi Scripts Using Roman Script

Leghari, Mehwish; Rahman, Mutee U

doi:10.32350/llr.12.03

Cited by 5 publications

(6 citation statements)

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“…This is mainly due to the language complexities, complex document layout and different unique characteristics associated to the Sindhi language. Handwritten Sindhi character recognition is more challenging than the printed Sindhi character recognition due to: (1) handwritten Sindhi characters have more variations in terms of aspect ratio when written by different writers or the same writer, (2) handwritten Sindhi text has no defined patterns and depends upon the quality of the writer's writing, (3) different shapes of the same character such as isolated, initial, medial and final make the recognition problem further complex (4) ligature overlapping makes the segmentation of characters more difficult (5) several characters have similar basic shape but they differ either by the number of dots or their positions around the shape, (6) it is cursive in nature and is written in the right to left direction (7) interconnections of two or more characters and several other challenges further reduce the recognition accuracy of handwritten Sindhi characters. Figure 1 shows different shapes of the same character used within a word, while Figure 2 shows the two groups of Sindhi characters with same baseline shape but different number of dots, orientations or their positions around the shape.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 1 shows different shapes of the same character used within a word, while Figure 2 shows the two groups of Sindhi characters with same baseline shape but different number of dots, orientations or their positions around the shape. The Sindhi is one of the ancient Indo-Aryan language and is spoken by more than forty million people in the Sindh province, Pakistan and some states of India (1) . It is a type of bidirectional cursive script, where the text is written in the right to left https://www.indjst.org/ direction and the numerals are written in the left to right direction.…”

Section: Introductionmentioning

confidence: 99%

“…It is a type of bidirectional cursive script, where the text is written in the right to left https://www.indjst.org/ direction and the numerals are written in the left to right direction. In Pakistan, it is written in Perso-Arabic style, while in India, it is written either in Devanagari or Perso-Arabic scripts (1) . The alphabet of the Sindhi language is mostly derived from the Arabic and Persian scripts with some additional letters which are neither present in the Arabic or Persian scripts.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Deep learning-based isolated handwritten Sindhi character recognition

Chandio¹,

Leghari²,

Panhwar³

et al. 2020

IJST

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Motivation : The problem of handwritten text recognition is vastly studied since last few decades. Many innovative ideas have been developed, where state-of-the-art accuracy is achieved for the English, Chinese or Indian scripts. The recent developments for the cursive scripts such as Arabic and Urdu handwritten text recognition have achieved remarkable accuracy. However, for the Sindhi script, existing systems have not shown significant results and the problem is still an open challenge. Several challenges such as variations in writing styles, joined text, ligature overlapping, and others associated to the handwritten Sindhi text make the problem more complex. Objectives: In this study, a deep residual network with shortcut connections and summation fusion method using convolutional neural network (CNN) is proposed for automatic feature extraction and classification of handwritten Sindhi characters. Method: To increase the powerful feature representation ability of the network, the features of the convolutional layers in the residual block are fused together and combined with the output of the previous residual block. The proposed network is trained on a custom developed handwritten Sindhi character dataset. To tackle the problem of small data, a data augmentation with rotation, flipping and image enhancement techniques have been used. Findings: The experimental results show that the proposed model outperforms than the best results previously published for the handwritten Sindhi character recognition. Novelty: This is the first research that proposes deep residual network with summation fusion for the Sindhi handwritten text recognition.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deep learning-based isolated handwritten Sindhi character recognition

Chandio¹,

Leghari²,

Panhwar³

et al. 2020

IJST

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“…In Sindhi Language 52 alphabetical letters (Fig. 1) were used for written as well as in speaking purposes [2][3][4]. Since, Sindh language contains more alphabetical letters than other languages, which causes difficulties for the new learners.…”

Section: Introductionmentioning

confidence: 99%

Identification of Issues and Challenges in Romanized Sindhi Text

Sodhar¹,

Hussain²,

Ibrahim³

et al. 2019

IJACSA

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Now-a-days Sindhi language is widely used in internet for the various purposes such as: newspapers, Sindhi literature, books, educational/official websites and social networks communications, teaching and learning processes. Having developed technology of computer system, users face difficulties and problems in writing Sindhi script. In this study, various issues and challenges come in the Romanized Sindhi text by using Roman transliteration (Sindhi text (ST) forms of Romanized Sindhi text) are identified. These acknowledged issues are known as noise, written script of Romanized and its style, space issues in Romanized script, some characters not suitable in Romanized Sindhi, as a paragraph, rows, character issues, punctuation, row break and font style. However, this study provides the summary of issues and challenges of Romanized Sindhi text. This research work provides detailed information of issues and challenges faced by people during chatting in Romanized Sindhi text.

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“…Sindhi Language is one the ancient Indus valley language having hundreds of years history and is widely spoken by approximately 40 million people in Sindh province of Pakistan, many states of India as well as various other areas of the world [4,5]. It is taught as a basic language in almost all the primary schools of Sindh province and is second largest spoken language in Pakistan.…”

mentioning

confidence: 99%

Multi-Digit Handwritten Sindhi Numerals Recognition using SOM Neural Network

Chandio¹,

Jalbani²,

Laghari³

et al. 2017

Mehran Univ. res. j. eng. technol.

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In this research paper a multi-digit Sindhi handwritten numerals recognition system using SOM Neural Network is presented. Handwritten digits recognition is one of the challenging tasks and a lot of research is being carried out since many years. A remarkable work has been done for recognition of isolated handwritten characters as well as digits in many languages like English, Arabic, Devanagari, Chinese, Urdu and Pashto. However, the literature reviewed does not show any remarkable work done for Sindhi numerals recognition. The recognition of Sindhi digits is a difficult task due to the various writing styles and different font sizes. Therefore, SOM (Self-Organizing Map), a NN (Neural Network) method is used which can recognize digits with various writing styles and different font sizes. Only one sample is required to train the network for each pair of multi-digit numerals. A database consisting of 4000 samples of multi-digits consisting only two digits from 10-50 and other matching numerals have been collected by 50 users and the experimental results of proposed method show that an accuracy of 86.89% is achieved.

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Towards Transliteration between Sindhi Scripts Using Roman Script

Cited by 5 publications

References 0 publications

Deep learning-based isolated handwritten Sindhi character recognition

Deep learning-based isolated handwritten Sindhi character recognition

Identification of Issues and Challenges in Romanized Sindhi Text

Multi-Digit Handwritten Sindhi Numerals Recognition using SOM Neural Network

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