ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021
DOI: 10.1109/icassp39728.2021.9414003
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One-Shot Conditional Audio Filtering of Arbitrary Sounds

Abstract: We consider the problem of separating a particular sound source from a single-channel mixture, based on only a short sample of the target source (from the same recording). Using SoundFilter, a waveto-wave neural network architecture, we can train a model without using any sound class labels. Using a conditioning encoder model which is learned jointly with the source separation network, the trained model can be "configured" to filter arbitrary sound sources, even ones that it has not seen during training. Evalu… Show more

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Cited by 19 publications
(33 citation statements)
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“…There are different ways to exploit the embedding vector within the extraction network [2,8,13]. We use here an elementwise multiplication ( operator in Fig.…”
Section: Soundbeammentioning
confidence: 99%
See 4 more Smart Citations
“…There are different ways to exploit the embedding vector within the extraction network [2,8,13]. We use here an elementwise multiplication ( operator in Fig.…”
Section: Soundbeammentioning
confidence: 99%
“…The embedding encoder computes the embedding vector e. There are two ways of estimating the embedding vector: using a 1-hot vector [7,9] or an enrollment audio sample [8]. We describe these two approaches in the following subsections.…”
Section: Soundbeammentioning
confidence: 99%
See 3 more Smart Citations