<![CDATA[Speech processing has become a significant study domain within signal processing, artificial intelligence, and human-computer interaction. This work does a bibliometric analysis to ascertain research trends, notable problems, and prospective directions in voice processing. We assess significant research outputs, including publication growth, influential authors, renowned journals, and collaboration networks during the last two decades, using data sourced from credible scientific sources such as Scopus and Web of Science. The results underscore notable progress in automated voice recognition, speaker identification, and speech synthesis, while simultaneously confronting ongoing issues associated with multilingual datasets, noise resilience, and resource efficiency. Moreover, new technologies, such deep learning and neural architecture search, are recognized as catalysts for future developments. This bibliometric study seeks to provide scholars and practitioners with a thorough overview of the existing environment and strategic insights for the advancement of the voice processing domain.]]>
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