Russian Alphabet Handwriting

Russian is a variation of the Cyrillic alphabet. It has a printed and script form, both of which have changed over time. The most important changes to be aware of are those made in the 1918 spelling revision that removed several letters.

I'm working on a Russian handwriting character recognition. For example, I have a picture of some letter and my system should recognize most of the symbols on this picture. I have a problem with datasets for recognition. I found some datasets for English handwriting symbols like this one. My question is: Where can I find datasets of Russian handwriting symbols because I failed to google it?

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Sure, that is an option. However my recommendation is to actually do it right as you are learning the alphabet. Learn to recognize that letter in printed and handwritten versions. Read the books, texts and practice your printed alphabet that way, but handwrite your answers, handwrite the new vocabulary, etc.

By slowing down and figuring out not only what the correct answer is, but how to properly write in in handwriting will actually help you pace yourself, pay more attention to your endings, your spelling and your sentence structure. And it will give you that extra time to absorb all the wonderful Russian vocabulary and rules.

The Russian language uses the Cyrillic alphabet. The version of the alphabet used today has thirty-three letters, which are listed in the chart below. Click on a letter to learn more about how it is formed and to see other examples of that letter in handwriting from historical records.

Despite the increasing use of tablets and laptops in schools, handwriting has maintained its central position in school education systems. Handwriting remains a paramount skill to be mastered in school since it is the basis of many core educational activities such as taking notes, composing stories and self-expression1,2,3. Handwriting is a complex perceptual-motor task, as it involves attention, perceptual, linguistic and fine motor skills4,5,6,7,8,9. Hence, even in typically developing children, learning handwriting usually begins around the age of five (pre-school) and last around 10 years10,11. During this time, handwriting evolves initially on a qualitative level (legibility) and then on a quantitative level (speed)12.

Many limitations come with the use of these tests. In addition to the subjectivity resulting from human scoring and time-consuming corrections, all of these tests are conducted using a pen/pencil and paper, meaning that their scoring is restricted to the analysis of the final, static handwriting product and does not consider or include any information about movement dynamics, which are crucial for the analysis of handwriting disorders20,21,22.

The development of digital tablets in the last decade has allowed us to tackle these problems since the dynamics of handwriting can now be assessed. Few handwriting tests for digital tablets have thus far been invented in different alphabets such as Latin or Hebrew21,23,24. In the model of interest for this study, Asselborn et al.21 extracted 53 features describing handwriting via different aspects and sorted them into four main categories, namely, static (which can possibly be measured with a pen/paper test), kinematic, pressure and tilt. These features were designed to capture low levels, almost physiological, aspects of handwriting (e.g. the micro-frequencies of shakiness) that are therefore independant of the shape of the letters and that could thus be transferred to other language and alphabets. In addition to reaching a remarkable accuracy in the binary diagnosis of severe handwriting difficulties (dysgraphia), the method can also characterize handwriting quality for the different features thanks to a comparison with normative children.

Our results are then discussed to see what implications the change in alphabet may have for the education of children in Kazakhstan, especially in terms of how handwriting difficulties are affected by the transfer in alphabet.

For every feature and for all grades (from 1st to 4th), a Wilcoxon test was conducted to detect if the distribution of a given feature in the Cyrillic alphabet is similar to the distribution of this same feature in the Latin alphabet. This statistical test was used since not all of the variables were found to follow a normal distribution. The results can be found in Table 1. In addition, the means and standard deviations for all distributions (by grade and alphabet) can be found in Supplementary Table S1.

Significant differences that could stem from intrinsic differences between the two alphabets were observed. Since the learning time difference between the two alphabets increased by grade (see Table 3), features that are different for all the grades (across four developmental ages) fall into this category (a typical example of such a feature can be found in Fig. 2C). Three of the four pressure and kinematic features, as well as one static feature, were regrouped into this category.

It is also very interesting to note the evolution of these features with grade. As illustrated in Fig. 2B, for both alphabets, a shift appears in the direction of handwriting proficiency with grade (the max speed of pressure change increases as children reach the higher grades). Even when there is an absolute difference between alphabets for this feature, its evolution follows the same path for both alphabets. In other words, this feature is still an indicator of handwriting automation for both alphabets even though a shift exists. This phenomena is shared with all the features described here.

Other pressure features seem to be affected by the difference in alphabet. The Nb of Peaks of Pressure Change Per Sec (#14) was found to be consistently higher when children were writing with the Cyrillic alphabet compared to when they were writing with the Latin alphabet, regardless of grade (see Supplementary Table S1). The Median of the Power Spectral of Pressure Frequencies (#15), a proxy for handwriting automation, was also found to be significantly different between the two alphabets whatever the grade. For these two features, however, no abnormalities were noted: If we interpret these features with the Latin model developed in Asselborn et al.21, then handwriting using the Cyrillic alphabet was found to be of higher quality. The Maximum Velocity (#7), always higher when children were writing in Cyrillic, can also be interpreted in the same manner (see Supplementary Table S1).

Two tilt features can also be sorted into this category. The Std. of Tilt-X (#16) and the Std. of Speed of Tilt-X change (#17) were always different between the two alphabets. Once again, children writing with the Cyrillic alphabet exhibited a higher standard deviation, which appears to be abnormal. In this sense, we believe that the difference comes from the alphabets requiring different pen manipulation styles (and thus pen tilts) during writing.

Finally, the Space Between Words (#3) feature was found to be consistently higher when children wrote in Cyrillic compared to Latin (see Supplementary Table S1). This feature computes the mean distance between strokes, which, in general, is the distance between words. In the case in which a word is composed of letters requiring writers to raise their pen in the middle, the distance traveled between the moment the pen rises and the pen touches the surface again is taken into account in the computation of this feature. We believe that the differences exhibited here signify more than an intrinsic difference between the two alphabets and that they are related to the difference in the learning times spent on each alphabet. Indeed, since our study provided their first opportunity to write in Latin, some children tended to write the letters one after the other with less continuity than they used when writing in Cyrillic (as can be seen in Fig. 3). Hence, there tended to be small distances between letters in words when writing with the Latin alphabet, which, when averaged, were responsible for the difference noted.

Some of the features exhibited decreasing differences between the two alphabets with grade. For instance, this trend can be seen in the two features describing shakiness: the Bandwidth of the Power Spectral of Tremor Frequencies (#1) and the Median of the Power Spectral of Tremor Frequencies (#2). As illustrated in Fig. 2D, the general trend show a decrease in the Median of the Power Spectral of Tremor Frequencies (#2) with grade, meaning that, for both alphabets, the average level of shakiness decreased with age, which is a direct consequence of the increasing level of automation children acquire. Interestingly, the difference between the two alphabets seems to decrease: children writing in Latin presented a significantly higher level of shakiness compared to when writing in Cyrillic in the lower grades (1st and second grade), while the difference was nearly non-existent by grade 4. Hence, the transfer between the two alphabets is in line with the level of automation. In other words, as automation increases, better control of the pen in one alphabet is beneficial for the other alphabet.

Other features seem to follow the same trend. Such is the case for the so-called In-Air-Time ratio (#8), a feature that was found to be highly correlated with handwriting problems in various studies conducted using the Latin alphabet21 as well as the Hebrew alphabet24,47. We can see that the In-Air-Time Ratio (#8) is always smaller for the Cyrillic alphabet (see Supplementary Table S1), which is a sign of a better knowledge of the Cyrillic alphabet by heart and of better motor program (memory) of the letters. Although the difference between the two alphabets was statistically significant for the lowest grade, no differences were found for subsequent grades.

Finally, the Handwriting Moment (#4) also falls into this category. Children were writing in "straight lines" to a greater degree when writing in the Cyrillic alphabet, which appears to be a normal result (writing in a straight line is an indicator of handwriting quality). The difference in "straightness" between the two scripts was found to decrease with grade. ff782bc1db