A Corpus-Based List of Frequently Used Words in Sesotho (2023)

Abstract: This paper describes the SpeechReporting Corpus, an online collection of corpora annotated for a range of discourse phenomena. The corpora contain folktales from 7 lesser-studied West African languages. Apart from its value for theoretical linguistics, especially for the study of reported speech, the database is an important resource for the preservation of intangible cultural heritage of minority languages and the development and testing of cross-linguistically applicable computational tools.

## introduction south african learners struggle with reading comprehension even when reading in their home languages @xcite . as a result, they perform poorly on problems involving language @xcite . this is especially pronounced in bilingual and multilingual learners since they develop literacy simultaneously in two languages @xcite . such learners perform more poorly than monolingual learners who get in-depth exposure to one language @xcite . this challenge of vocabulary and language demands is increased when south african learners with indigenous languages as their first languages move from the third to the fourth grade of education and where the language of instruction changes from indigenous languages to either english or afrikaans @xcite . according to @xcite , 78% of south african fourth graders were unsuccessful at extracting meaning from texts. unfortunately, not being able to extract meaning from texts puts learners at risk of not being able to read as their lack of vocabulary affects their ability to read texts with desirable fluency @xcite . sadly, learners' inability to read with the expected level of fluency and their inability to extract meaning from texts makes it difficult for teachers and assessors to choose reading passages. reading interventions to assist learners with less-thandesired reading abilities are needed in most language classes. unfortunately, teachers may not always be well-trained to teach reading and monitor reading interventions @xcite . furthermore, teachers' levels of command may not always allow for successful interventions @xcite . for higher pass rates, one might have to resort to using texts expected to be administered to learners with fewer years of schooling. this is particularly unfavourable for research on the development of reading metrics for south african indigenous languages. consistent estimations of readability levels are essential in educational contexts where instructors and examiners need to identify and assign texts to readers with specific levels of education. such consistency in assigning readability estimations prevents instances where learners in higher grades are assigned texts that are easier to read than those that are assigned to learners in lower grades. without readability metrics, authors, publishers, and readers may not always estimate readability levels accurately or consistently @xcite . unfortunately, as far as we are aware, there are no readability metrics for sesotho. one solution to this may be the development of classical readability formulas. classical readability metrics use mathematical formulas to estimate the level of education or the grade that a reader needs in order to read a specific text with ease @xcite . these linear regression formulas are normally based on superficial text properties such as lengths of words, sentences, syllables, and frequency lists. fortuitously, sentence and word lengths can easily be determined using universal preprocessing tools as they are language-independent. however, determining syllables and frequently used words requires specific language tools. as far as could be ascertained for this article, there are two syllabification systems for sesotho, see @xcite . as such, sesotho syllable information can be extracted from texts. unfortunately, there is no frequency-based list of the most used words to use in readability studies. looking at existing readability formulas, one of the most well-known frequency lists is the one developed by @xcite . the strategy to compile this list was to directly present these words in reading to 4th-grade learners, a word made it to the list when it was known by at least 80 per cent of the children @xcite @xcite . ideally, when devising a word list for sesotho (or other indigenous languages) a similar technique should be used. unfortunately, such a user-based approach may yield regressive results since the majority of learners in indigenous african language classes have low reading abilities and vocabulary knowledge @xcite . in other words, the result of a user-based approach would be a list of reading entry-level words. this article presents our efforts to create a list of the 3000 most frequently used words in written sesotho using a corpus analysis approach. we position our work in research on adapting readability metrics (section 2). we then present our methodology for creating the list (section 3) and subsequently discuss the results (section 4). we conclude our article by highlighting the strengths of the list and by formulating a set of suggestions for further improvements (section 5). ## related work digital language resources and human language technologies audits for south african languages indicate that all indigenous languages of south africa are under-resourced @xcite @xcite . more specifically, @xcite reviewed the basic language resource kit for sesotho and concluded that many necessary digital language resources are still lacking. a few studies have assessed the readability of sesotho texts using english readability metrics. for instance, @xcite manually extracted textual properties used in classical readability metrics to investigate the readability of sesotho health pamphlets. in another study, @xcite developed a sesotho health literacy test. unfortunately, the studies used english metrics without considering the differences between sesotho and english textual properties. therefore, the results from these studies may have misrepresented the context of sesotho's written texts. furthermore, due to the lack of resources, manual methods for extracting textual properties were used which is highly impractical to be used at a large scale and error-prone. multiple studies have explored the adaptation of classical readability metrics to lower-resourced languages. for norwegian, @xcite explored the adaptation of eight classical readability metrics, namely, the automated readability index (ari) @xcite , coleman-liau index (cli) @xcite , flesch reading ease (fre) @xcite , flesch-kincaid grade level (fkgl) @xcite , gunning fog index (gfi) @xcite , lasbarhetsindex (lix) @xcite , rate index (rix) @xcite , and simple measure of gobbledygook (smog) @xcite . almost all those metrics were originally developed for english, except for lix and rix which were developed for swedish. one of their most important findings was that syllable counts and complex words did not have the same effect on readability levels in norwegian as they did in the english metrics. in the end, only the swedish lix and rix metrics could successfully be adapted to the lower-resourced norwegian. the english fre and fkgl formulas have also been adapted to @xcite . in this process, the two text characteristics that are included in the formulas, i.e. average sentence and word length, were compared and the corresponding weights adapted @xcite . similarly, the english fre has been adapted to dutch, by both douma @xcite and brouwer @xcite , who each assigned slightly different weights in order to account for the differences in word and sentence length between english and dutch. the popular fre formula has also been adapted to french @xcite , czech @xcite and italian @xcite . a study by @xcite revealed that the outcomes of classical formulas developed for english, dutch and swedish on dutch data yield strong correlations, which is explained by the formulas' strong reliance on certain languageindependent properties, such as average word or sentence length. however, failed attempts of adapting classical readability metrics using higherresourced languages have also been reported. for instance, @xcite reports an unsuccessful attempt at adapting the english fre, gfi, fkgl and smog metrics into hindi and bangla. they concluded that new metrics which are based on bangla and hindi structural properties should be developed as the existing metrics yield out-ofbound results. new textual properties such as juktaakshars were then introduced in the resulting hindi metrics. this implies that readability metrics can be adapted when there is comparability such as in the cases of english, dutch and swedish, which are all germanic languages. however, new formulas may need to be developed when language structures are incomparable such as in the case of hindi and english. moreover, certain popular classical formulas also comprise variables based on frequency lists. the most well-known formula in this respect is the dale-chall reading grade score @xcite . besides relying on average sentence length, this formula also counts how many words occur in the dale-chall word list. this list comprises 3,000 words which are known in reading by at least 80 per cent of fourth-grade children. an updated version of the list was published in 1995 @xcite . the dale-chall formula or index is one of the most used metrics in health information @xcite . given that the formula was originally developed to assess reading material for children, it is recommended to adjust the formula, and especially the list of frequently used words when using it to measure readability for specific target audiences @xcite . on the other hand, the list of common words has been criticised for failing to account for specialised meanings @xcite . in this work, we wish to explore whether a similar list can be created for sesotho. ideally, we would like to also assess the word list with users such as school learners. even so, before testing can begin, we need an initial list. we are also concerned that testing the list on school learners may be challenging due to the recently implemented gate-keeping procedures aimed at protecting vulnerable participants in the post-pandemic era. nevertheless, we are exploring other user tests that could make our list applicable to other target audiences, such as adult readers, authors, and publishers. currently, there exist at least two lists of frequently used words in sesotho, namely the most-commonwords foot_0 and the waston chen foot_1 list. however, a few issues arise when consulting these lists. first of all, both lists have been (machine) translated from english into sesotho, which means they are less representative of the sesotho language. moreover, for some of the translations in the waston chen list, sepedi is being used (such as kgauswi instead of sesotho haufi 'near'). because of this translation from english into sesotho both lists also contain various entries which are not single words but phrases. for instance, the waston chen list mentions yuniti eno ya thuto 'that unit of the lesson' for the english 'unit' entry. similarly, the mostcommonwords list also mentions a sebetsang a 'that work' for the english entry 'active'. the lists also inconsistently interchange between two different orthographies, both the lesotho sesotho and the south african sesotho orthography are being used. finally, for both lists, it is difficult to find any background information on how the original lists were actually created. we, therefore, believe that a more structured and purposed development of a frequency list is needed and opt for a corpus-based approach in this paper. ## methodology we collected a total of three corpora which comprise original sesotho text material, see ## results and discussion as mentioned above the three frequency lists were merged and relative frequencies were calculated for duplicate entries. afterwards, a qualitative analysis was carried out on all entries, which is presented next. ## discussion and conclusion this article discussed the development of a list of frequently used words in sesotho using a corpusbased approach. three different corpora were employed to this end. although possibly unconven-tional the bible corpus has also been included in this investigation and the results seem to confirm that this corpus behaves somewhat differently. nevertheless, we believe the inclusion of this corpus is fitting for sesotho as new orthographies were introduced using bible translations (makutoane, 2022). for instance, the south african sesotho orthography was introduced through the 1960 bible translation. initially, we also wished to incorporate texts from the sesotho wikipedia. however, upon closer inspection, it was found that the orthography used in the wiki pages represents both sesotho from south africa and sesotho from lesotho depending on who did the translation and/or initial editing of the wikipedia entry. such inconsistencies in the orthography may result in misrepresented frequencies. although some inconsistencies between the orthographies may be semi-automatically corrected, others need a case-by-case analysis. the aim of designing objective methods for measuring text readability in sesotho is to enable teachers and assessors, in general, to be able to choose educational texts consistently and fairly. in reality, it is difficult to find texts in an under-researched language such as sesotho. finding new texts for learners is not always easy for teachers. in the end, texts are re-used without being re-adjusted to learners' reading abilities. even so, texts prepared by examiners and textbook compilers at national and provincial levels re-purpose literary texts such as novels and dramas together with magazine and newspaper articles. some of the texts are even translated from online english texts. the extent to which these texts are suitably adapted to specific learners has not been investigated. the presence of an empirically developed frequency list such as the one presented in this article allows for taking further steps towards developing classical readability metrics which use frequency lists. although the texts used for our corpus analysis contain a vast amount of government texts, we believe the final list does not necessarily solely represent government texts, because the meanings of the words are taken out of context. for instance, words such as leleme 'tongue/language/gossiper', and moputso 'salary/wage/payment/reward/gain', which both appear on our list, are not only used in government texts. furthermore, the frequency list from the bible corpus overlapped with more than a third of the frequency lists of the other two corpora. this is an indication that the words are not necessarily restricted to government texts and that the list may be relevant for use even in other contexts such as educational texts. in future work, the frequency list will be further validated on a corpus of education texts @xcite , and be incorporated into adaptations of several readability formulas requiring frequency word lists from english to sesotho. furthermore, the list will be tested on envisaged end-users such as learners, teachers and publishers for further validation.