Acoustic signal compression techniques, converting the floating-point waveform into the bitstream representation, serve a cornerstone in the current data storage and telecommunication infrastructure. The rise of data-driven approaches for acoustic coding systems brings in not only potentials but also challenges, among which the model complexity is a major concern: on the one hand, this general-purpose […]
Kai Zhen is a Ph.D. candidate (ABD), advised by Prof. Minje Kim, in Computer Science and Cognitive Science at Indiana University. He has been working on efficient and scalable neural waveform coding systems. He had two machine learning and relevance internships at LinkedIn in 2018 and 2019, trailed by an internship at Amazon Alexa in 2020.