328 citations · 883 across the 52 of their papers we have counts for
6 papers · 1 filter
Quantifying the Uncertainty of Blindly Estimated Room Embeddings Using a Dispersion-Calibrated Score
Yang Xiang, Philipp Götz, Emanuël A. P. Habets +3
Room embeddings derived from reverberant speech are often unreliable: speech content and recording degradation can alter the representation even when speaker, room, and source-rece…
Scattering in Feedback Delay Networks
Sebastian J. Schlecht, Emanuël A. P. Habets
Feedback delay networks (FDNs) are recursive filters, which are widely used for artificial reverberation and decorrelation. One central challenge in the design of FDNs is the gener…
Deep Filtering: Signal Extraction and Reconstruction Using Complex Time-Frequency Filters
Wolfgang Mack, Emanuël A. P. Habets
Signal extraction from a single-channel mixture with additional undesired signals is most commonly performed using time-frequency (TF) masks. Typically, the mask is estimated with…
Multi-Speaker Localization Using Convolutional Neural Network Trained with Noise
Soumitro Chakrabarty, Emanuël A. P. Habets
The problem of multi-speaker localization is formulated as a multi-class multi-label classification problem, which is solved using a convolutional neural network (CNN) based source…
Broadband DOA estimation using Convolutional neural networks trained with noise signals
Soumitro Chakrabarty, Emanuël. A. P. Habets
A convolution neural network (CNN) based classification method for broadband DOA estimation is proposed, where the phase component of the short-time Fourier transform coefficients…
Near-field signal acquisition for smartglasses using two acoustic vector-sensors
Dovid Y. Levin, Emanuël A. P. Habets, Sharon Gannot
Smartglasses, in addition to their visual-output capabilities, often contain acoustic sensors for receiving the user's voice. However, operation in noisy environments may lead to s…