Sanna starts her internship at Spotify in NYC.

Minje received an NSF grant for an exciting multidisciplinary research project, “A Portable and Intelligent Testing System for Power-efficient and Accurate Foodborne Pathogen Detection,” in collaboration with the fellow Engineering faculty, Lei Jiang (PI) and Feng Guo.

Minje organized Midwest Music and Audio Day along with other faculty members in the school. He presented the recent deep autotuner research results, too.

A new speech coding paper, “Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding,” was accepted for publication in Interspeech 2019.

The Ph.D. students in SAIGE work as an intern in various research labs in the industry this summer: Amazon (Sanna), LinkedIn (Kai), Qualcomm (Sunwoo), and Spotify (Aswin).

We are attending ICASSP 2019 in Brighten, UK. Minje will chair a session on source separation and speech enhancement; Sunwoo and Sanna will present their papers about bitwise recurrent neural networks and a database of quality Karaoke singing, respectively.

The Deep Autotuner project got featured on BBC Radio 5 Live “Drive (from 1:27:09),”The Times, Daily Mail, and the New Scientist magazine. It also got featured on School’s news page.

Our papers are accepted for publication in ICASSP 2019: “Incremental Binarization On Recurrent Neural Networks for Single-Channel Source Separation” and “Intonation: a Dataset of Quality Vocal Performances Refined by Spectral Clustering on Pitch Congruence.”

A fun collaboration with folks in the Sunflower state resulted in a paper in RTCSA. It’s about DeepPicar, a deep learning based low powered autonomous driving system: “DeepPicar: A Low-cost Deep Neural Network-based Autonomous Car”

Our paper is accepted for publication in EUSIPCO 2018: Sanna Wager and Minje Kim, “Collaborative speech dereverberation: regularized tensor factorization for crowdsourced multi-channel recordings.”