With new age speakers such as the Echo Dot and Google Home, everyone should have equal opportunity to use them. Yet, for many popular voice recognition systems, the only accents that have wide support are those from Europe, Latin America, and Asia. This can be frustrating for users who have dialects or accents which are poorly understood by common tools like Amazon's Alexa. As such devices become more like household appliances, researchers are becoming increasingly aware of bias and inequity in Speech Recognition, as well as other sub-fields of Artificial Intelligence. The addition of African accents can potentially diversify smart speaker customer bases worldwide. My research project can help developers include accents from the African diaspora as they build these systems. In this work, we measure recognition accuracy for under-represented dialects across a variety of speech recognition systems and analyze the results in terms of standard performance metrics. After collecting audio files from different voices across the African diaspora, we discuss key findings and generate guidelines for developing an implementation for current voice recognition systems that are more fair for all
