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The number of older adults is growing significantly worldwide. At the same time, technological developments are rapidly evolving, and older populations are expected to interact more frequently with such sophisticated systems. Automated speech recognition (ASR) systems is an example of one technology that is increasingly present in daily life. However, age-related physical changes may alter speech production and limit the effectiveness of ASR systems for older individuals. The goal of this paper was to summarize the current knowledge on ASR systems and older adults. The PRISMA method was employed and 17 studies were compared on the basis of word error rate (WER). Overall, WER was found to be influenced by age, gender, and the number of speech samples used to train ASR systems. This work has implications for the development of future human-machine technologies that will be used by a wide range of age groups.

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