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Design of an Optimal Hindi Keyboard for Convenient and Efficient Use
Abstract
In this paper, we present a new design of the Hindi keyboard for convenient typing. We describe the ergonomic criterion we have used to evaluate and compare keyboards. This criterion is a mathematical formulation of keyboard optimality in terms of the distribution of the typing effort among the ten fingers, accessibility of commonly used keys and various other factors. Measured against this criterion, our keyboard performs more than twice as better than the standard Hindi keyboard. We also describe a genetic algorithm based optimization framework which we use to arrive at our new keyboard design. Finally, we perform some sensitivity analysis on our optimization procedure and demonstrate that our results confirm to intuitive expectations.
... Eggers et al. (2003) used a more sophisticated model and precisely defined six ergonomic criteria, namely, the tapping load distribution, number of keystrokes, hand alternation, finger alternation, finger posture, and hit direction. Deshwal and Deb (2003) used Eggers' criteria as the performance indices and developed a near-optimal Hindi keyboard. ...
... Some of the existing solutions to the KAP used heuristics such as n-opt (Lesher et al., 1998), entropy minimization (Tanaka-Ishii et al., 2002), and multi-start descent algorithm (Sorensen, 2007). Alternating proposals applied metaheuristic techniques including genetic algorithms (Deshwal and Deb, 2003;Minneman, 1985;Oommen et al., 1989), simulated annealing (Light and Anderson, 1993;Li et al., 2006), and ant colony optimization Wagner et al., 2003). In this paper, we adopt the Cyber Swarm metaheuristic which is inspired from the particle swarm optimization to solve the keyboard arrangement problem. ...
... The first category addresses the functionality according to ergonomic criteria while the second group aims at maximizing the effectiveness of disambiguation/prediction. We consider both categories of objectives and they are described as follows. Eggers et al. (2003) used six Marsan's ergonomic criteria (tapping load distribution, number of keystrokes, hand alternation, finger alternation, finger posture, and hit direction) in designing an SCK which was subsequently adopted in designing a Hindi keyboard by Deshwal and Deb (2003). Based on the six Marsan's ergonomic criteria, we present two ergonomic performance indexes that is applicable in general keyboard arrangement context. ...
Traditional QWERTY keyboard has been known to be an ill design due to its low typing speed, fatigue-inducement, no reference to learnability, to name a few. Many researchers have put their effort on optimizing the character arrangement of the keyboard by taking into account the co-occurrence frequency of characters in words, typing ergonomics, and word disambiguation effectiveness. However, most of the existing works addressed the problem for a single objective instead of multiple ones, and the design of customized keyboards for motor-impaired users is often overlooked. In this paper, we propose a general mathematical model that integrates varying keyboard arrangement context. A Cyber Swarm method considering multiple objectives is proposed and it can create additional benefits that cannot be obtained by traditional methods. Our Cyber Swarm method accommodates ergonomic criteria and disambiguation/prediction effectiveness simultaneously. Experimental results manifest that the Cyber Swarm keyboard outperforms several benchmark keyboards and other competing algorithms. We also show an illustrative example for preliminary keyboard shape design which could be very useful in customized keyboard production for motor-impaired users whose physical capacity has been evaluated a priori. Finally, an empirical experiment involving human subjects is performed in order to analyze the feedbacks from humans’ experiences in using the new keyboard layouts.Relevance to industryUsing the proposed general framework for keyboard arrangement, various scenarios (for example, single-character or multi-character keys, single-finger or multi-finger typing) raised in industrial production can be all taken into account without the hassle to change solution methods for different settings. Hence, the time and costs in industrial production for customized keyboard is significantly reduced.
... If the QWERTY layout, which was developed based on the English language, is inconsistent with it, then regarding other languages, it does not occur differently. This limitation encouraged research that both investigated and developed new keyboard layout proposals suitable for other languages [Liao and Choe 2013, Deshwal and Deb 2003, Khorshid et al. 2010. Such investigations are based on concepts of ergonomics and contemplate the use of Genetic Algorithms (GA) to find an optimized keyboard layout solution. ...
... Most publications in this research area are based on statistical data, assessing the frequency of letters and sequences of each language, and then applying some optimization process, based on specific factors and criteria. Some examples of studies were found in the literature that optimized the keyboard layout for Chinese [Liao and Choe 2013], Hindi [Deshwal and Deb 2003], and Arabic [Khorshid et al. 2010]. However, was not found in literature an attempt to apply this methodology for Brazilian Portuguese, being one of the objectives of this paper to fill this gap. ...
Currently, keyboards are the most common means of communicating with computers. Despite being the most commonly used keyboard layout, QWERTY has had various issues raised concerning its effectiveness, as it is not efficient in English (target language) or in fact other languages. Therefore, this paper presents the development process of a Genetic Algorithm with the intention of generating a more adequate and coherent layout proposal for Brazilian Portuguese, which has its focus on ergonomics and user productivity. Using five ergonomic criteria and a statistical analysis of the characters and sequences of most frequently used pairs in Brazilian Portuguese, a layout approximately 53% better than QWERTY was obtained.
... Deshwal and Dep [3], designed an optimal Hindi keyboard layout using a GA. The aim was to reach a keyboard layout that is better than the currently used one. ...
... GAs are known to be successful in solving difficult optimization problems, like the QAP. In additions, for the keyboard layout problem, a GA approach was used to optimize the m-finger Arabic keyboard in [9,13], the m-finger Persian keyboard in [15], and the m-finger Hindi keyboard in [3]. Nevertheless, to the best of our knowledge, it has not been previously attempted for s-finger keyboards. ...
The use of cellphones and handheld devices in our daily activities is not
limited to making calls or writing short text messages. The added features of wireless
technology and related applications made it possible to write emails, notes and
long text. Nevertheless, the currently used keyboards in portable devices are not
optimized for such use, in terms of rapid and ergonomic typing. In this research,
we aim to optimize the design of the Arabic keyboard layout for applications that
predominantly use a single pointer, such as those used in portable devices. The
main objective is to find the best single-finger Arabic keyboard layout that allows
users of portable devices to write text and carry out written conversations for a
long time with comfort, ease, and speed. Since the single-finger keyboard layout
problem can be modeled in terms of the famous Quadratic Assignment Problem
(QAP), which is known to be NP-hard, heuristics and meta-heuristics are recommended
for solving such problem. To adapt the problem to the requirements of
optimizing the single-finger Arabic keyboard, we added two measures to the classical—
distance based—objective function of the QAP, which are: the keyboard
row weight and the hit direction of the finger. A Genetic Algorithm (GA) approach
with two different crossover types (two-point and modified uniform crossovers),
and three different mutation operators (swap, insertion, and Simulated Annealing
(SA)) was developed and thoroughly tested. The experimental results demonstrated
that the simple swap mutation produced better results than the other mutations,
with both crossover types. Moreover, experimental testing has shown that the
added measures in the objective function had a positive effect, in terms of improving
the typing speed, when compared to the original QAP objective function.
... Goetti et al. proposed a genetic algorithm to reach an English keyboard layout that was better than current one [6]. Deshwal and Deb, designed an optimal Hindi keyboard for convenient and efficient use using a steady-state Genetic Algorithm [7]. They used ergonomic criterion to evaluate and compare keyboards. ...
Acquiring a suitable keyboard layout is an optimization problem that different methods have been offered to solve it. As the answer is the most appropriate permutation for letters on the keyboard, that it is 33 letters for Persian keyboard. In this paper, a Persian keyboard layout has been proposed using Evolutionary Strategy(ES) that has been improved for typing speed and it rectified some problems of current layout. The used fitness function, calculates typing time for any Persian letter pairs. This function uses some parameters like hand transition, finger transition, finger weight and so on. The experimental results show that the proposed algorithm, attains a Persian keyboard layout that is faster than the current layout and other layouts that have been acquired in related works.
... The objective of optimization in a traditional keyboard is to arrange the characters on the keys in a manner that is most efficient in terms of typing time and effort [1]. It has been observed that the utilization of this traditionally designed keyboard for prolonged gaming purposes leads to musculoskeletal disorders arising from repetitive stress injuries. ...
The average gamer faces a number of musculo-skeletal injuries due to bad design of keyboards, consoles, mice, workspace layout and a number of other factors. This study aims at minimizing injuries and maximizing human comfort by using Ergonomic principles in the design of the console, which also happens to be the main interactive device between the gamer and the computer. Hence the objective of this study would be to design a keyboard to optimize the comforts of using a gaming console for computer games played on the keyboard, through the sciences of anthropometry and ergonomics.
... Genetic algorithms have been successfully used in solving the QAP. In addition, a GA was applied to solve the m-finger Persian keyboard in [12], the m-finger Hindi keyboard in [13], and the m-finger Arabic keyboard in [2] [7]. As far as we know, it has not been previously used in the optimization of s-finger keyboards in any language. ...
Cellular phones and other hand-held devices are now extensively used to write emails, notes and long texts. However, the arrangement of keys in the current keyboards is not optimized to facilitate rapid and ergonomic typing. In this paper, we aim to optimize the Arabic keyboard layout for applications that predominantly use a single pointer. The single-finger keyboard layout problem can be modeled in terms of the Quadratic Assignment Problem (QAP), which can be solved using metaheuristic algorithms. To adapt the problem to the requirements of optimizing the single-finger keyboard, we used three measures in our objective function: the distance between pairs of letters, a weight for each row in the keyboard, and the hit direction of the finger. A Genetic Algorithm (GA) approach with two crossover types (2-point and modified uniform crossovers) and two different mutation operators (swap and insertion) was developed and thoroughly tested. The performance of the Genetic Algorithm was also compared against a Simulated Annealing (SA) algorithm using the same objective function. Moreover, we developed a Memetic Algorithm combining GA and SA to maximize the chances of obtaining good solutions. We compared our resulting optimized keyboard layouts with different existing and proposed layouts. The comparison results show that our keyboard layouts are more efficient, in terms of the optimization criteria considered, than the tested layouts. Finally, the performance of our keyboards was tested by virtually estimating the speed of typing. Our keyboards also outperform other layouts in terms of the measured typing speed. The details of the algorithms and the experimental results are reported in this paper.
... However, a detailed analysis of whether these are truly optimal or better arrangements exist, has not been done. Most of this research has been in two broad directions: Normal Keyboards Ambiguous Keyboards [7] Another constraint in spread of Hindi over the WEB is that of limited content. Where there are more than 20 billion pages on web in English, this number is not more than 10 million in Hindi. ...
With the internet growing at an exponential rate the web is increasingly hosting web pages in different languages. It is essential for the search engines to be able to search information stored in a specific language. The native users also tend to look for any information on web nowadays. This leads to the need of effective search engines to fulfill native user's needs and provide them information in their native languages. The major population of India use Hindi as a first language. The Indian constitution identifies 22 languages, of which six languages (Hindi, Telugu, Tamil, Bengali, Marathi and Gujarati) are spoken by at least 50 million people within the boundaries of the country—there are a large number of them living outside the country. The Hindi language web information retrieval is not in a satisfactory condition. The presence of Hindi on the World Wide Web is still limited and tentative because of attitudinal and technical factors. Besides the other technical setbacks the Hindi language search engines face the problem of morphology, phonetics, word sense disambiguation etc. The performance of search engines is affected by these problems. This paper covers the comprehensive analysis and also the comparison of the affect of language structure related factors (morphology, phonetics, WSD, synonyms,) on the performance of search engines supporting Hindi language.
... The literature sources could vary from newspapers, electronic books, scientific journals, etc. Wagner et al. (2001), used Le Monde, Der Spiegel, and USA Today newspapers for French, German, and English text sources, respectively. On the other hand, Deshwal and Deb (2004) used various text sources from the internet (15 MB of text ISCII format) for an Indian keyboard design. Mrayati (1990) showed marginal difference in both monographs and digraphs frequencies for texts resources taken from three different Arab countries. ...
A new design of Arabic keyboard layout for convenient typing and effective use of keyboard is proposed. The design methodology is based on ergonomic criteria that evaluate and compares different keyboard layouts for optimal characters distribution. The proposed design criteria are simulated by a mathematical model that uses: 1) best distribution of the typing effort among the ten fingers of the typist; 2) accessibility of commonly used characters; 3) various other factors as constraint equations to reach an optimal keyboard layout that is ergonomically improved. This task is carried out using a genetic algorithm based optimisation framework. The new keyboard layout shows better ergonomic performance than the present keyboard being used in Arabic world with a 36.3% improvement.
... Deshwal and Deb [1] described a steady-state genetic algorithm that searched for good keyboard layouts of the Devanagari script in which Hindi is written. The GA represented key arrangements as four-dimensional arrays and applied mutation, crossover, and local search operators tailored to this representation. ...
Keyboard design is a combinatorial problem of perennial interest to those who work with computers. An evolutionary algorithm can search a space of key arrangements for one that is easy to use. Its genotypes represent candidate keyboards, and its fitness function measures the difficulty of typing a specified body of text. Here, a genetic algorithm seeks to arrange the twenty-six letter and six punctuation marks (four of the latter in two pairs) on three rows of ten keys each. It encodes keyboards as permutations of key positions. Its evaluation function considers the relative loads on the hands, consecutive keystrokes by one hand or finger, and the relative difficulties of using individual fingers as it simulates typing a block of text. In tests using a concatenated body of text and its three components (a collection of message logs, Moby Dick, and the King James Bible), the GA consistently evolved keyboards with markedly better evaluations than either the QWERTY or Dvorak keyboards, though the GA's keyboards differed depending on the text it used in its evaluation function.
This study suggests a new keyboard layout to efficiently type in Chinese characters. The layout was based on a statistical analysis of Chinese corpus and was derived from a genetic algorithm. In the semantic analysis, 6 million Chinese characters were transcribed into typing script. Macros of polyphone were disambiguated from either the context or the presence probabilities in the training data. Relative frequencies of single letter and letter pair were counted to investigate on tapping workload and sequence. In the genetic algorithm, five ergonomics criteria—tapping workload distribution, hand alternation, finger alternation, avoidance of big steps, and hit direction—were applied to evaluate keyboard layout alternatives. The result showed that the proposed layout is 43% better than the QWERTY layout in terms of the weighted sum of the five ergonomic criteria.
Many persons with disabilities lack the fine motor coordination necessary to operate traditional keyboards. For these individuals, ambiguous (or reduced) keyboards offer an alternative access method. By placing multiple characters on each key, the size and accessibility of the individual keys can be enhanced without requiring a larger keyboard. Using statistical disambiguation algorithms to automatically interpret each keystroke, these systems can approach the keystroke efficiency (keystrokes per character) of conventional keyboards. Since the placement of characters on each key determines the effectiveness of these algorithms, several methods of optimizing keyboard arrangements have previously been proposed. This paper presents a new method for optimizing an arbitrary set of N characters over a collection of M keys. While earlier efforts relied upon approximations of keystroke efficiency, the proposed approach optimizes the arrangement under this exact performance measure. Applied to the canonical 26 characters on a nine-key "telephone keypad" problem, this method provides an improvement in efficiency of 2.5 percentage points over previously established layouts. Using only a minimum of calculations, the proposed technique operates quickly and efficiently, deriving optimal arrangements in a matter of seconds using a personal computer. The flexible method is applicable to arbitrary disambiguation algorithms, character sets, and languages.
In a ten-session experiment, six participants practiced typing with an expanding rehearsal method on an optimized virtual keyboard. Based on a large amount of in-situ performance data, this paper reports the following findings. First, the Fitts-digraph movement efficiency model of virtual keyboards is revised. The format and parameters of Fitts' law used previously in virtual keyboards research were incorrect. Second, performance limit predictions of various layouts are calculated with the new model. Third, learning with expanding rehearsal intervals for maximum memory benefits is effective, but many improvements of the training algorithm used can be made in the future. Finally, increased visual load when typing previously practiced text did not significantly change users' performance at this stage of learning, but typing unpracticed text did have a performance effect, suggesting a certain degree of text specific learning when typing on virtual keyboards.
The arrangement of letters on a keyboard greatly influences the user's comfort and typing speed. With repetitive muscular injuries emerging and the amount of text to be treated increasing, the need for a better arrangement has come forth. To solve the problem, a non-trivial abstract representation of a physical keyboard layout and of type-writing rules is introduced. Having justified the choice of heuristic ergonomic criteria, a mathematical function for the ergonomic evaluation criteria is developed. Based on the ant colony optimization algorithm, an optimization algorithm is designed and applied to the problem described. The computational results representing the quality of the keyboard arrangements obtained for several languages are finally discussed and new solutions for optimization of the keyboard are presented.
The physical arrangement of characters on keyboards contributes to the efficiency and rate at which messages can be generated. While this is true for any individual and any keyboard, character arrangement can have a particularly profound impact on persons with disabilities who utilize only a single finger (or headstick, mouthstick, laser pointer, etc.) for key selection. We propose a new method for optimizing character arrangement on a fixed set of keys, based loosely on the pioneering work of Levine and Goodenough-Trepagnier. By repeatedly swapping the positions of different character pairs (or triplets) and re-evaluating the efficiency of the arrangement, our technique rapidly converges on the most efficient character layout. This method is applicable to any keyboard and can be tailored to the specific motor tendencies of a particular user or class of users.
Application of genetic algorithms to the keyboard optimization problem
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Designing better keyboards
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Designing better keyboards. AI Expert
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