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Found 5 papers, 1 papers with code
Upmixing via style transfer: a variational autoencoder for disentangling spatial images and musical content
In the stereo-to-multichannel upmixing problem for music, one of the main tasks is to set the directionality of the instrument sources in the multichannel rendering results.
Dereverberation using joint estimation of dry speech signal and acoustic system
The purpose of speech dereverberation is to remove quality-degrading effects of a time-invariant impulse response filter from the signal.
Deep Autotuner: a Pitch Correcting Network for Singing Performances
We train our neural network model using a dataset of 4, 702 amateur karaoke performances selected for good intonation.
Fully Learnable Front-End for Multi-Channel Acoustic Modeling using Semi-Supervised Learning
Using a large offline teacher model trained on beamformed audio, we trained a simpler multi-channel student acoustic model used in the speech recognition system.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Deep Autotuner: A Data-Driven Approach to Natural-Sounding Pitch Correction for Singing Voice in Karaoke Performances
This approach differs from commercially used automatic pitch correction systems, where notes in the vocal tracks are shifted to be centered around notes in a user-defined score or mapped to the closest pitch among the twelve equal-tempered scale degrees.
