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\"Yoruba, one of the national languages of Nigeria, is spoken by more than 30 million people worldwide. It is the most widely spoken language in Nigeria after English, and is also spoken in Benin and Togo. This unique, two-part resource provides travelers to Nigeria and other parts of West Africa with the tools they need for daily interaction. The bilingual dictionary has a concise vocabulary for everyday use, and the phrasebook allows instant communication on a variety of topics. Ideal for businesspeople, travelers, students, and aid workers, this guide includes: 4,000 dictionary entries; phonetics that are intuitive for English speakers; Essential phrases on topics such as transportation, dining out, and business; Concise grammar and pronunciation sections.\"--Provided by publisher.

This is the first comprehensive account of prolonged hearing loss and its impact on a language that was once spoken fluently. Although it is currently assumed that hearing loss results in speech deterioration, it is shown that language loss occurs when speakers remain deaf for a long time. The reader is introduced to a significant deaf population — postlingually deafened Yoruba speakers who have been deaf for more than twenty years and who have no access to hearing aids or speech therapy. After becoming deaf, they continue to speak Yoruba from memory and \"hear\" visually through lip reading. These speakers exhibit phonological, lexical and syntactic losses which mirror acquisition patterns attested in the speech of Yoruba children. Based on these similarities, it is argued that a direct link exists between language loss and first language acquisition. It is further argued that prolonged deafness results in language reversal. Finally, the book presents the first description of the sign language and gestures used by deafened speakers to augment their spoken language. These findings will be of value to linguists, speech, language and hearing therapists, anthropologists, Africanists, deaf studies researchers, and non-specialists who are interested in hearing health and wellness.

Natural language processing (NLP) has the potential to promote public health. However, applying these technologies in African health systems faces challenges, including limited digital and computational resources to support the continent's diverse languages and needs. This scoping review maps the evidence on NLP technologies for public health in Africa, addressing the following research questions: (1) What public health needs are being addressed by NLP technologies in Africa, and what unmet needs remain? (2) What factors influence the availability of public health NLP technologies across African countries and languages? (3) What stages of deployment have these technologies reached, and to what extent have they been integrated into health systems? (4) What measurable impact has these technologies had on public health outcomes, where such data are available? (5) What recommendations have been proposed to enhance the quality, cost, and accessibility of health-related NLP technologies in Africa? This scoping review includes academic studies published between January 1, 2013, and October 3, 2024. A systematic search was conducted across databases, including MEDLINE via PubMed, ACL Anthology, Scopus, IEEE Xplore, and ACM Digital Library, supplemented by gray literature searches. Data were extracted and the NLP technology functions were mapped to the World Health Organization's list of essential public health functions and the United Nations' sustainable development goals (SDGs). The extracted data were analyzed to identify trends, gaps, and areas for future research. This scoping review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guidelines, and its protocol is publicly available. Of 2186 citations screened, 54 studies were included. While existing NLP technologies support a subset of essential public health functions and SDGs, language coverage remains uneven, with limited support for widely spoken African languages, such as Kiswahili, Yoruba, Igbo, and Zulu, and no support for most of Africa's >2000 languages. Most technologies are in prototyping phases, with only one fully deployed chatbot addressing vaccine hesitancy. Evidence of measurable impact is limited, with 15% (8/54) studies attempting health-related evaluations and 4% (2/54) demonstrating positive public health outcomes, including improved participants' mood and increased vaccine intentions. Recommendations include expanding language coverage, targeting local health needs, enhancing trust, integrating solutions into health systems, and adopting participatory design approaches. The gray literature reveals industry- and nongovernmental organizations-led projects focused on deployable NLP applications. However, these projects tend to support only a few major languages and specific use cases, indicating a narrower scope than academic research. Despite growth in NLP research for public health, major gaps remain in deployment, linguistic inclusivity, and health outcome evaluation. Future research should prioritize cross-sectoral and needs-based approaches that engage local communities, align with African health systems, and incorporate rigorous evaluations to enhance public health outcomes. RR2-doi:10.1101/2024.07.02.24309815.

A deeply informed Afrocentric view of language and cultural retention under slavery.Maureen Warner-Lewis offers a comprehensive description of the West African language of Yoruba as it has been used on the island of Trinidad in the southern Caribbean.

A deeply informed Afrocentric view of language and cultural retention under slavery. Maureen Warner-Lewis offers a comprehensive description of the West African language of Yoruba as it has been used on the island of Trinidad in the southern Caribbean. The study breaks new ground in addressing the experience of Africans in one locale of the Africa Diaspora and examines the nature of their social and linguistic heritage as it was successively retained, modified, and discarded in a European-dominated island community.

This article provides a description and an Optimality Theory (OT) analysis of contact-induced changes and variation in contemporary Yoruba syllable structure. The article claims that a major diachronic change has occurred in the syllable structure of Yoruba phonology due to its continued contact with English, resulting in the invention, preservation, and hypercorrection of clusters and codas. I characterize this change in terms of OT constraint re-ranking (Miglio and Moren 2003) and assess the resulting synchronic variation against the indexed constraint approach of Itô and Mester (1995a, b, 1999), the ranked-winners approach of Coetzee (2004), the partial-order co-phonology of Anttila (1997), and the Maximum Entropy (MaxEnt) model of Goldwater and Johnson (2003). I show that none of these approaches is able to account independently for the categorical, gradient, and lexically conditioned variation that characterize the contemporary Yoruba syllable structure, but rather that a MaxEnt model augmented with lexical indexation is the most economical model that fits the Yoruba data accurately.

The rich diversity of human language allows speakers to seamlessly transition between multiple languages during conversations. While humans have the remarkable ability to become proficient in multiple languages in a short period, developing machines that can converse in multiple natural languages with an understanding of diverse dialects requires sophisticated Natural Language Processing (NLP) techniques such as dialect recognition and intent extraction. This facilitates mutual understanding between parties who use phrases, sentences, words, or expressions from multiple languages within a single context. The work in this paper, propose a trilingual approach to multi-dialect conversation modeling within the same conversational session and context for a mix of English, Hindi–English text, Hindi–Devanagari text and Yoruba text. The model identifies the language used and determines the intent behind a query to respond in the same dialect. Our model is capable of detecting the end of a conversation, and it also detects the predominant dialect and responds accordingly in scenarios where a user’s input query contains a mix of languages. This approach is particularly useful in situations where there is limited data available for multilingual or trilingual conversation tasks based on Intent Detection (ID). We evaluate our proposed pipeline and model on three benchmark ID datasets and a trilingual dialogue dataset for response retrieval by intent decoding. Our model outperforms existing approaches in terms of performance metrics and has faster training time. Moreover, our trilingual approach to multi-dialect conversation modeling provides a versatile tool for efficient and effective inter-dialect conversational automation, even when dealing with large datasets, with minimal parameters and low resource overhead. The lightweight architectural pipeline and efficient algorithms used in our model contribute to its high performance and versatility.

This paper examines inflection in the Ào dialect of Yorùbá, a language spoken in south west Nigeria. Previous studies in Yorùbá morphology have focused on derivational morphology rather than inflectional morphology. This work revealed that, in the Ào dialect, some functional categories have inflectional properties known as replasive morphemes. These funtional categories are the pronoun (both long and short), tense markers, aspect markers as well as focus and imperative markers. In this paper, we discussed the various forms of these words and the environments of their occurrence.

This paper explores the intricate interplay between living with mental illness and the processes of identifying mental illness in Abeokuta, Nigeria. With a particular focus on the contextual understanding of personhood, this study reveals how sociocultural backgrounds modulate the understanding of mental illness and its treatments within the Yoruba context. Through nine months of ethnographic fieldwork and discursive narrative analysis, the research revealed that becoming a mentally ill person is deeply intertwined with the everyday social life in the study site. The analysis highlights the multifaceted nature of personhood, encompassing various aspects such as parenthood, friendship, employment, and financial freedom. These facets of personhood are shaped by specific social practices and embedded within complex webs of social relations, often becoming more pronounced when these relationships are disrupted, leading to certain behaviours being categorised as mental illness. This paper underscores the significance of recognising and acknowledging the contextual notion and understanding of mental illness to ensure the provision of acceptable and effective care and recovery strategies.

This paper presents novel data from a Yorùbá language game called Enà, an iterative affixation game that typically involves copying of vowels and tones onto a dummy syllable. Yorùbá VV sequences are all analyzed as disyllabic in existing literature, yet we find that Enà treats them differently depending on their provenance: underlying VV sequences, those created from pronouns, and those derived through floating tone are treated as a single locus of insertion, as variably are those that share tone, while VV sequences derived through consonant deletion or compounding are generally treated as two separate loci. We argue that the difference indicates that Yorùbá in fact has long vowels, contrary to previous assumptions. We analyze the pattern in Optimality Theory, following Krämer & Vogt's (2018) analysis of reduplicative language games but adding a reduplicative template and back-copying, and we consider the implications of the pattern and analysis to the study of Yorùbá and the study of language games.