The number of people who speak Yoruba language fluently and write it correctly with appropriate tonal signs is declining. This could be attributed to the adoption of English Language (a colonial language) by parent as their children first language and the neglect of Yoruba from most Nigeria Educational system curricula. To this end, the aim of this work was to improve user knowledge of tonal sign assigning, correct word pronunciation and thus Yoruba language literacy by implementing a Computer Assisted Language Learning System that translates Yoruba text to speech, and allows users to check-up the meaning of words and take test on Yoruba language literacy. We propose a practical iterative learning approach that factors in the basic features and requirements that will ensure the optimal realization of benefits of the system to the user. • Computing methodologies ➝Artificial intelligence ➝Natural language processing ➝Machine translation Indigenous languages as Children's first language and making Indigenous languages a compulsory course to be taken by students in all level of education. However, there is need for more efforts that will adopt practical approach to ensure that the language remains intact. To this end, Computer Assisted Language Learning (CALL) for Yoruba is developed in this project to help speakers of Yoruba language to speak correctly and fluently by applying the appropriate tone on words they pronounce. CALL is perceived as an approach to language teaching and learning in which the computer is used as an aid to the presentation, reinforcement and assessment of material to be learned, usually including a substantial interactive element [4]. The computer is used to ameliorate users' knowledge of particular Language/languages. CALL has being continually adopted as medium of learning new languages or improving on old ones. Over the years CALL is used to incite language learners, provide comfortable access to learning material, testing of users acquisition level and examining the relevance of call to Learning and Disseminating System (Checking if it has accomplish its functions and purpose). The CALL system provided information which is expected to be responded to by system users. The system in turn process input and gives appropriate justification of input structure and meaning. To improve Flexibility of Computer Assisted Language Learning Interaction between system and users have being adopted, text, static and moving images and audio are used for interactive Computer Assisted Learning Language System Environment. By adopting a practical iterative learning approach, this work focuses on improving user knowledge of Yoruba tonal sign assigning, correct word pronunciation. It also improves Yoruba language literacy by implementing a Computer Assisted Language Learning System that translates Yoruba text to speech, and allows users to check-up the meaning of words and undertake test on Yoruba language literacy.
Yoruba tribe makes up about 35 million people in total with
majority constituent from Nigeria (about 21% of Nigeria's
population), 1.2 million in Benin, 0.4 million in Ghana, 0.1
million in Togo )0.1 million in Ivory Coast, 0.2 million in Europe
and 0.2 million in North America [
There is a continued decline in the number of "Yorubas" that can speak Yoruba language fluently and write it correctly with appropriate tonal signs. This is as a result of adoption of English Language (a colonial language) by parent as their children first language and the neglect of Yoruba from most Nigeria Educational system curricula.
To prevent extinction of Nigeria's indigenous languages there have being persistent calls by various esteemed scholars and organisation to revive Nigeria indigenous languages, by adopting
Previous studies have focused on CALL by identifying three
historical phases of CALL and classified them according to
underlying pedagogical and methodological approaches [
An Intelligent CALL System for Arabic Learners was designed for
Primary Schools and Arabic language learners. The system
employed Natural Language Processing for learning the language
and provides learning materials for the users, on which they are
expected to take test on. The instructor is able to stipulate
conditions to determine the test questions specialisation. The
response given by users is analysed using morphological analyser,
syntax analyser and semantic analyser. The morphological
analyser breaks down response of the users to smallest component
of the language. The syntax analyser checks for the structural
correctness of user's response and form syntactic categories. The
Semantic analyser checks for rule based approach to generate
appropriate response to result given by the system users to
promote effective learning. [
The principles of Natural Language Processing and Digital Signal
Processing was adopted to develop a CALL system [
A web based Computer Assistance Language Learning on two
languages was built, to translate from Yoruba phrases to English
Language and contra wise [
Yoruba language is a tonal language consisting of seven oral vowel sounds, five nasal vowels and eighteen consonant sounds and 3 tonal signs (three level tones: high, low and mid (the default tone) to distinguish between words with the same spelling but different pronunciation and meaning. Every Yoruba syllable must have at least one tone.
b, d, f, g, gb, j, k, l, m, n, p, r, s, ṣ, t, u, w, y
Oral vowel: a e ẹ Nasal vowel: an ẹn in i
o ọn un ọ u
The framework of Yoruba Computer Assisted Language Learning (YorCALL), as shown in figure 1, presents the different components and their interactions. Sectionalized into three, the framework can be viewed as: Front end Interactive interface (YorCALL Interface) Modules (Palindrome, Class, Game, Learn & Dictionary) and Back end (YorCALL Database) The YorCALL interactive interface provides the user with an interface to enter any Yoruba text with the use of on-Screen keyboard or the provided buttons with Yoruba alphabets and sign. The YorCALL Database mainly consist all the Yoruba syllable sounds as recorded by a Yoruba Language expert from Oyo town. The Learn & Dictionary modules provide the users with basic knowledge on the meaning of most common Yoruba words such as cardinal and ordinal numbers from one to ten and days of the week and months of the year as well as English words listed in alphabetical order from A-Z with information about them. It consists of 1000 English words and their equivalent in Yoruba language. Users are able to hear the corresponding pronunciation of the words. The Palindrome module responds to indicate whether any Yoruba word as entered by the user is/is not a palindrome.
The CLASS module provides principles of pronouncing words in Yoruba language and also provides guide on the principle of tonal signs and applications. It allows the user to write down words, check for validity and pronounce the word for the user. As depicted in figure 2, YorCALL a) breaking words into syllable b) fetching the audio equivalent of syllable c) stacking and concatenating sounds to produce a word sound Users are can type in words for pronunciation by using the onscreen keyboard provided or use any keyboard that allows user to type Yoruba fonts. The words are broken down to syllable(s) and equivalent audio sound of the syllable is fetched and concatenated. After which a sound player box pops up and users are able to play the sound.
A syllable in Yoruba can either be a vowel sound, combination of vowel and consonant, or nasal sound. During the process of breaking words down to syllables, the tonal sounds assigned by the user is taken into consideration. Each word input by the user is scanned through, vowel letters are the main unit is used for tokenisation.
The tokenization process is broadly divided in three phases, namely: i. accept word ii. scan from the left, check for vowel sounds ii. anywhere there is a vowel sound break, and then add to syllable set until end of the word.
Accept text
N End of Text?
Y For Illustration, if b is to be combined with the vowel sounds; it will produce the following syllables as in table 1:
Each of the vowel sounds was combined with each consonant and nasal sound to generate all possible syllable. These sounds to each syllable were recorded using audio recorder by a Yoruba language speaking expert. The recorded sounds were subsequently trimmed to eliminate noise and saved in the YorCALL DB with the file name they represent. The Token/syllable fetchers searches through for the coreesponding audio sound for each token for stacking and concatenation. 3.1.3 Syllable to Speech Processor
After successful process of tokenisation and equivalent audio system’s processes inclsuoduen:d of the syllables are fetched from the audio dataset, they are stacked in the order of their entry (from left to right) and concatenated, ready to be played by the sound player box. Users are able to view the breakdown of words pronunced to syllable and play the sound equivalent as often time as possible as shown in Figure 6.
SS1 +
SS2 +
SS3 …+…
SSn Where SS represents syllable sound
YorCALL has five classes (Class, Palindrome, Dictionary, Learn, Games) which are subclasses of the Home. The Sound Player is a sub class of the Class with a modal dependency. As shown in Figure 4, each class has at least member methods with data member ranging from zero to six.
The user enters a yoruba text with the customized keyboard provided as shown in Figure 2 which allows the entering of any Yoruba word. On clicking the ‘check’ button, the tokenize() method is called and the inputted text is syllabilized.
Three category of users (amateur speakers, average Yoruba speakers, above average speakers) yielded the following summarized responses as observed in Table 2:
X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14
Questionnaire (Source: [
The study has presented a CALL system for Yoruba language with the main objective of providing a digital learning environment that introduce Yoruba language to new learner or improve amateur's knowledge, especially in the area of correct word pronunciation and right sign assigning. Using personal computer, the system enables the user to learn at his/her own time and place. Future work is ongoing to expand the number of words in the dictionary and improve on present functionalities of the system such as development of game whereby the system pronounce Yoruba words randomly and the user provides the textual equivalence, considering the tone, wherby the user input is validated. In conclusion we believe the system can be further scaled to include other threatened languages and taught in various levels of Institutions of learning. We appreciate all members of Intelligent System group (ISG) for their insightful contributions towards this work.