5 citations · 6 across the 5 of their papers we have counts for
14 papers
Learned complex masks for multi-instrument source separation
Andreas Jansson, Rachel M. Bittner, Nicola Montecchio +1
Music source separation in the time-frequency domain is commonly achieved by applying a soft or binary mask to the magnitude component of (complex) spectrograms. The phase componen…
Relational Weight Priors in Neural Networks for Abstract Pattern Learning and Language Modelling
Radha Kopparti, Tillman Weyde
Deep neural networks have become the dominant approach in natural language processing (NLP). However, in recent years, it has become apparent that there are shortcomings in systema…
Anti-Transfer Learning for Task Invariance in Convolutional Neural Networks for Speech Processing
Eric Guizzo, Tillman Weyde, Giacomo Tarroni
We introduce the novel concept of anti-transfer learning for speech processing with convolutional neural networks. While transfer learning assumes that the learning process for a t…
Multi-Time-Scale Convolution for Emotion Recognition from Speech Audio Signals
Eric Guizzo, Tillman Weyde, Jack Barnett Leveson
Robustness against temporal variations is important for emotion recognition from speech audio, since emotion is ex-pressed through complex spectral patterns that can exhibit signif…
Weight Priors for Learning Identity Relations
Radha Kopparti, Tillman Weyde
Learning abstract and systematic relations has been an open issue in neural network learning for over 30 years. It has been shown recently that neural networks do not learn relatio…
Making Good on LSTMs' Unfulfilled Promise
Daniel Philps, Artur d'Avila Garcez, Tillman Weyde
LSTMs promise much to financial time-series analysis, temporal and cross-sectional inference, but we find that they do not deliver in a real-world financial management task. We exa…