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Both internal factors (e.g., nonverbal intelligence) and external factors (e.g., input quantity) are claimed to affect the rate of children's vocabulary development. However, it remains an open question whether these variables work similarly on bilingual children's dual language learning. The current paper examined this issue on 805 Singapore children (4 years, 1 month to 5 years, 8 months) who are learning English (societal language) and an ethnic language (Mandarin/Malay/Tamil). Singapore is a bilingual society; however, there is an inclination for English use at home in recent years, resulting in a discrepancy of input between English and ethnic languages in many families. In this study, internal and external factors were examined comprehensively with standardized tests and a parental questionnaire. Regression analysis was used to address the questions. There were statistically significant differences in language input quantity, quality, and output between English and ethnic language learning environments. Singapore children are learning English in an input-rich setting while learning their ethnic language in a comparatively input-poor setting. Multiple regressions revealed that while both sets of factors explained lexical knowledge in each language, the relative contribution is different for English and ethnic languages: internal factors explained more variance in English language vocabulary, whereas external factors were more important in explaining ethnic language knowledge. We attribute this difference to a threshold effect of external factors based on the critical mass hypothesis and call for special attention to learning context (input-rich vs. input-poor settings) for specific bilingual language studies.

This study modeled vocabulary trajectories in 91 English language learners (ELLs) with Punjabi, Tamil, or Portuguese home languages, and 50 English monolinguals (EL1) from Grades 1 to 6. The concurrent and longitudinal relationships between phonological awareness and phonological short-term memory and vocabulary were examined. ELLs underperformed EL1s on vocabulary across all grades. Although vocabulary grew faster in ELLs than in EL1s in the primary grades, they did not close the gap after 6 years of English schooling. Mutual facilitation was found between phonological awareness, English-like nonwords, and vocabulary. A unidirectional relationship was found between Hebrew-like nonwords and vocabulary suggesting that the relationship between phonological short-term memory and vocabulary can be more accurately captured when using nonwords based on a remote, unfamiliar language.

Child characteristics, family factors, and preschool factors are all found to affect the rate of bilingual children's vocabulary development in heritage language (HL). However, what remains unknown is the relative importance of these three sets of factors in HL vocabulary growth. The current study explored the complex issue with 457 Singaporean preschool children who are speaking either Mandarin, Malay, or Tamil as their HL. A series of internal factors (e.g., non-verbal intelligence) and external factors (e.g., maternal educational level) were used to predict children's HL vocabulary growth over a year at preschool with linear mixed effects models. The results demonstrated that external factors (i.e., family and preschool factors) are relatively more important than child characteristics in enhancing bilingual children's HL vocabulary growth. Specifically, children's language input quantity (i.e., home language dominance), input quality (e.g., number of books in HL), and HL input quantity at school (i.e., the time between two waves of tests at preschool) predict the participants’ HL vocabulary growth, with initial vocabulary controlled. The relative importance of external factors in bilingual children's HL vocabulary development is attributed to the general bilingual setting in Singapore, where HL is taken as a subject to learn at preschool and children have fairly limited exposure to HL in general. The limited amount of input might not suffice to trigger the full expression of internal resources. Our findings suggest the crucial roles that caregivers and preschools play in early HL education, and the necessity of more parental involvement in early HL learning in particular.

This study examines the effectiveness of the Tamil-English Bilingual Method on vocabulary acquisition among Tamil- medium higher secondary school students in Tamil Nadu. Vocabulary development is a critical component of second language learning, particularly in contexts where exposure to English outside the classroom is limited. A quasi- experimental design was employed, with two groups of students (N = 30 each) selected from comparable schools. The control group received instruction through conventional English-only methods, while the experimental group was taught using the Tamil–English Bilingual Method, which strategically employed Tamil as a scaffold to introduce and reinforce English vocabulary. Pre-test and post-test scores were analyzed to measure vocabulary gains. The results revealed a significant difference between the groups. While the control group showed minimal improvement, the experimental group displayed a statistically significant increase in vocabulary acquisition. The bilingual approach not only enhanced comprehension and retention but also increased learner confidence in using new vocabulary. The findings suggest that bilingual instruction provides meaningful contextual support, allowing students to connect prior knowledge in their mother tongue with new linguistic input in English. This method holds particular promise for rural and low-English- exposure contexts in Tamil Nadu, where students face challenges in developing adequate English proficiency. By integrating the mother tongue in vocabulary instruction, teachers can create a more inclusive and effective learning environment. The study highlights the potential of bilingual pedagogy as a practical and culturally responsive strategy to strengthen English language education in similar multilingual contexts.

The influence of home and community factors in predicting ethnic or heritage language vocabulary were examined among 282 Singaporean children whose ethnic languages (or mother tongues) were Chinese, Malay, or Tamil, and who were also learning English. The results indicated that (1) parents speaking ethnic language to children had a strong positive effect on children’s ethnic language vocabulary, whereas parents speaking only English had a negative effect; (2) language community had an effect on children’s ethnic language vocabulary, which may reflect community support for the language among the broader community; (3) family income worked differently depending on the language community; and (4) watching television in English mostly/only had a negative effect on children’s ethnic language vocabulary. These findings lend support to other studies among language-minority children indicating that maintaining an ethnic or heritage language requires home support when schooling is through a societally dominant language.

This paper presents an open source and extendable Morphological Analyser cum Generator (MAG) for Tamil named ThamizhiMorph. Tamil is a low-resource language in terms of NLP processing tools and applications. In addition, most of the available tools are neither open nor extendable. A morphological analyser is a key resource for the storage and retrieval of morphophonological and morphosyntactic information, especially for morphologically rich languages, and is also useful for developing applications within Machine Translation. This paper describes how ThamizhiMorph is designed using a Finite-State Transducer (FST) and implemented using Foma. We discuss our design decisions based on the peculiarities of Tamil and its nominal and verbal paradigms. We specify a high-level meta-language to efficiently characterise the language’s inflectional morphology. We evaluate Thamizhi-Morph using text from a Tamil textbook and the Tamil Universal Dependency treebank version 2.5. The evaluation and error analysis attest a very high performance level, with the identified errors being mostly due to out-of-vocabulary items, which are easily fixable. In order to foster further development, we have made our scripts, the FST models, lexicons, Meta-Morphological rules, lists of generated verbs and nouns, and test data sets freely available for others to use and extend upon.

Three common assumptions concerning bilingual children’s language proficiency are: (1) their proficiency in two languages is usually unbalanced; (2) low socioeconomic status (SES) indicates low proficiency in both languages; and (3) encouraging parents to speak some societal language at home will promote its development. Examining the vocabulary scores of 282 bilingual Singaporean kindergartners (167 Chinese, 70 Malay, and 45 Tamil), the current study found that these young children were evenly divided among four language profiles: strong in ethnic language (Chinese, Malay or Tamil) or English, strong in both languages, or weak in both. Children with high proficiency in both languages were proportionally represented in the low, middle and high SES groups, demonstrating the achievability of strong vocabulary in two languages for children of different SES. However, low SES children were most at risk for low proficiency in both languages, although many achieved high proficiency in ethnic language or both. Middle and high SES children were most likely to demonstrate low ethnic language with high English proficiency. Children mostly exposed to one language from different sources generally showed strength in that language. Children exposed to both languages at home were most likely to show low proficiency in both languages, although plenty of children exposed to both languages developed high proficiency in English or both. These results affirm previous findings that SES and home language exposure influence bilingual children’s proficiency. Implications include the importance of teachers assessing bilingual children’s proficiency in both languages and collaborating with parents to develop bilingual children’s vocabulary.

Culture and language evolve together. With respect to Tamil, the form of the language that people use nowadays has come a long way from its origins. These days, the old literary form of Tamil is used commonly for writing and the contemporary colloquial Tamil is used for speaking. Human–computer interaction applications require colloquial Tamil (CT) to make it more accessible and easy for the everyday user and, it requires literary Tamil (LT) when information is needed in a formal written format. Continuing the use of LT alongside CT in computer-aided language learning applications will both preserve LT, and provide ease of use via CT, at the same time. Hence, there is a need for the conversion between LT and CT dialects, which demands as a first step, dialect identification. Dialect identification (DID) of LT and CT is an unexplored area of research. There is a considerable research potential in this area, because, (i) LT is standardized while CT is not fully standardized and, (ii) they have only subtle differences. Five methods are explored in our work, which originated from the preliminary work using Gaussian mixture model (GMM) for dialect identification of LT and CT, which offered a motivation with an identification accuracy of 87%. In the current work, keeping the nuances of both these dialects in mind, one other implicit method—convolutional neural network (CNN); two explicit methods—Parallel Phone Recognition (PPR) and Parallel Large Vocabulary Continuous Speech Recognition (P-LVCSR); two versions of the proposed explicit unified phone recognition method (UPR-1 and UPR-2), are explored. These methods vary based on: the need for annotated data, the size of the unit, the way in which modelling is carried out, and the way in which the final decision is made. Even though the average duration of the test utterances is less—4.9 s for LT and 2.5 s for CT—the systems performed well, offering the following identification accuracies: 87.72% (GMM), 93.97% (CNN), 89.24% (PPR), 94.21% (P-LVCSR), 88.57 (UPR-1), 93.53% (UPR-1 with P-LVCSR), 94.55 (UPR-2) and 95.61% (UPR-2 with P-LVCSR).

To code-switch or not to code-switch? This is a dilemma for many bilingual language teachers. In this study, the influence of teachers’ CS on bilingual children's language and cognitive development is explored within heritage language (HL) classes in Singapore. Specifically, the relationship between children's language output, vocabulary development, and cognitive flexibility to teachers’ classroom CS behavior, is examined within 20 preschool HL classrooms (10 Mandarin, 6 Malay, and 4 Tamil). Teachers’ and children's utterances were recorded, transcribed, and analyzed for CS frequency and type (i.e., inter-sentential, intra-sentential). 173 students were assessed with receptive vocabulary and dimensional card sort tasks, and their vocabulary and cognitive switching scores assessed using correlational and mixed effects analyses. Results show that inter-sentential and intra-sentential CS frequency is positively and significantly related to children's intra-sentential CS frequency. Overall, findings revealed that teachers code-switched habitually more often than for instructional purposes. Neither inter-sentential nor intra-sentential CS was significantly related to children's development in HL vocabulary, and intra-sentential CS was found to positively and significantly relate to children's growth in cognitive flexibility. These findings reveal the multi-faceted impact of teacher's CS on children's early development.