2 citations · 3 across the 3 of their papers we have counts for
4 papers
Latent Variable Algorithms for Multimodal Learning and Sensor Fusion
Lijiang Guo
Multimodal learning has been lacking principled ways of combining information from different modalities and learning a low-dimensional manifold of meaningful representations. We st…
Deep Autotuner: A Data-Driven Approach to Natural-Sounding Pitch Correction for Singing Voice in Karaoke Performances
Sanna Wager, George Tzanetakis, Cheng-i Wang +3
We describe a machine-learning approach to pitch correcting a solo singing performance in a karaoke setting, where the solo voice and accompaniment are on separate tracks. The prop…
A Data-Driven Approach to Smooth Pitch Correction for Singing Voice in Pop Music
Sanna Wager, Lijiang Guo, Aswin Sivaraman +1
In this paper, we present a machine-learning approach to pitch correction for voice in a karaoke setting, where the vocals and accompaniment are on separate tracks and time-aligned…
Bitwise Source Separation on Hashed Spectra: An Efficient Posterior Estimation Scheme Using Partial Rank Order Metrics
Lijiang Guo, Minje Kim
This paper proposes an efficient bitwise solution to the single-channel source separation task. Most dictionary-based source separation algorithms rely on iterative update rules du…