Unknown attribute values in induction
Proceedings of the sixth international workshop on Machine learning
Incremental Singular Value Decomposition of Uncertain Data with Missing Values
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Learning from Incomplete Data
Audio imputation using the non-negative hidden markov model
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
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With the recent attention towards audio processing in the time-frequency domain we increasingly encounter the problem of missing data within that representation. In this paper we present an approach that allows us to recover missing values in the time-frequency domain of audio signals. The presented approach is able to deal with real-world polyphonic signals by operating seamlessly even in the presence of complex acoustic mixtures. We demonstrate that this approach outperforms generic missing data approaches, and we present a variety of situations that highlight its utility.