5 papers
Mind the Microphone Gap: Benchmarking Array Upsampling Strategies for Latent Acoustic Mapping
Philipp Schmidt, Huw Cheston, Juan Azcarreta +3
Latent Acoustic Mapping (LAM) is a self-supervised learning method that generates high-resolution spherical acoustic maps from multichannel recordings without labelled data, matchi…
Sound Event Detection with Boundary-Aware Optimization and Inference
Florian Schmid, Chi Ian Tang, Sanjeel Parekh +9
Temporal detection problems appear in many fields including time-series estimation, activity recognition and sound event detection (SED). In this work, we propose a new approach to…
More Than A Shortcut: A Hyperbolic Approach To Early-Exit Networks
Swapnil Bhosale, Cosmin Frateanu, Camilla Clark +7
Deploying accurate event detection on resource-constrained devices is challenged by the trade-off between performance and computational cost. While Early-Exit (EE) networks offer a…
Controlling the Parameterized Multi-channel Wiener Filter using a tiny neural network
Eric Grinstein, Ashutosh Pandey, Cole Li +6
Noise suppression and speech distortion are two important aspects to be balanced when designing multi-channel Speech Enhancement (SE) algorithms. Although neural network models hav…
Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem
Andres Fernandez, Juan Azcarreta, Cagdas Bilen +1
Recent work in online speech spectrogram inversion effectively combines Deep Learning with the Gradient Theorem to predict phase derivatives directly from magnitudes. Then, phases…