Kai Zhen

Ph.D. Candidate in Computer Science and Cognitive Science at Indiana University.

Research Group: Signals & Artificial Intelligence Group in Engineering (SAIGE)
Email: ZHenK At IU doT EdU
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Research interests

I conduct research on audio and acoustic signal processing in the current deep/machine learning paradigm, with the focus on both model capacity and efficiency. Concretely, I've been working on cross-module residual learning that is compatible with both advanced, fast changing data-driven modules and conventional methodologies in audiology for lightweight speech coding. In terms of monaural speech enhancement, we proposed a hybrid architecture incorporating both CNN and RNN in a densely connected manner to enable dual-level context aggregation, efficiently. Besides, I worked a psychoacoustically weighting scheme to prioritize the model training towards an energy efficient speech denoising autoencoder. My supervisor is Prof. Minje Kim.

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