Towards Yorùbá-speaking Google maps navigation

Abstract Advances in natural language processing (NLP) have made several technological interventions and services available to people in different languages. One such service is the Google Maps direction narration which provides real-time oral assistance to tourists, and visitors in a new or unknown location. Like most related assistive technologies, this service is primarily developed in the English language with support for some other Western languages over time, and the African languages are largely neglected. This paper seeks to leverage advances in NLP techniques and models in the design of a speech-to-speech (STS) translation of the Google Maps direction narration in English to the Yoruba language, one of the most widely spoken languages in Western Africa. We begin with an exploration of various state-of-the-art NLP techniques for Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-speech (TTS) models that make up the designed system. We presented the performance of the models we explored towards the design and implementation of a robust STS translation of the Google Maps direction narration in the Yoruba language.