8 citations · 23 across the 21 of their papers we have counts for
24 papers
Frequency-Weighted Soft-Constrained Spatially Selective Active Noise Control for Open-Fitting Hearables
Tong Xiao, Reinhild Roden, Matthias Blau +1
Recently, soft-constrained spatially selective active noise control (SSANC) for open-fitting hearables has been proposed to enable a flexible trade-off between noise reduction and…
A Study on Online Mask-based Beamforming Using Per-channel Masking for Spatially Distributed Microphones
Wiebke Middelberg, Svantje Voit, Simon Doclo +1
Mask-based beamforming is a popular geometry-agnostic approach for speech enhancement, typically applying a single mask across all microphones to estimate the required covariance m…
In-the-Loop Training of Deep Feedback Cancellation for Hearing Aids
Svantje Voit, Simon Doclo
Acoustic feedback limits the maximum gain in hearing aids. In addition to several approaches based on adaptive filtering, recently a deep-neural-network-based feedback cancellation…
Flexible Multi-Channel Target Speaker Extraction Using Geometry-Conditioned Spatially Selective Non-linear Filters
Jiatong Li, Wiebke Middelberg, Simon Doclo
Recently, a spatially selective non-linear filter (SSF) has been proposed for target speaker extraction, using the target direction-of-arrival (DOA) as a spatial cue. Since learned…
Robust Soft-Constrained Spatially Selective Active Noise Control for Hearables Under Secondary Path Variations
Tong Xiao, Reinhild Roden, Matthias Blau +1
Spatially selective active noise control (SSANC) hearables aim to attenuate noise from certain directions at the eardrum while preserving desired speech arriving from selected dire…
Distributed Multichannel Wiener Filtering for Wireless Acoustic Sensor Networks
Paul Didier, Toon van Waterschoot, Simon Doclo +4
[This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.] In a wireles…
I-DCCRN-VAE: An Improved Deep Representation Learning Framework for Complex VAE-based Single-channel Speech Enhancement
Jiatong Li, Simon Doclo
Recently, a complex variational autoencoder (VAE)-based single-channel speech enhancement system based on the DCCRN architecture has been proposed. In this system, a noise suppress…
Subjective quality evaluation of personalized own voice reconstruction systems
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo +1
Own voice pickup technology for hearable devices facilitates communication in noisy environments. Own voice reconstruction (OVR) systems enhance the quality and intelligibility of…
A Steered Response Power Method for Sound Source Localization With Generic Acoustic Models
Kaspar Müller, Markus Buck, Simon Doclo +2
The steered response power (SRP) method is one of the most popular approaches for acoustic source localization with microphone arrays. It is often based on simplifying acoustic ass…
Binaural Localization Model for Speech in Noise
Vikas Tokala, Eric Grinstein, Rory Brooks +4
Binaural acoustic source localization is important to human listeners for spatial awareness, communication and safety. In this paper, an end-to-end binaural localization model for…
Binaural Speech Enhancement Using Complex Convolutional Recurrent Networks
Vikas Tokala, Eric Grinstein, Mike Brookes +3
From hearing aids to augmented and virtual reality devices, binaural speech enhancement algorithms have been established as state-of-the-art techniques to improve speech intelligib…
Comparison of Knowledge Distillation Methods for Low-complexity Multi-microphone Speech Enhancement using the FT-JNF Architecture
Robert Metzger, Mattes Ohlenbusch, Christian Rollwage +1
Multi-microphone speech enhancement using deep neural networks (DNNs) has significantly progressed in recent years. However, many proposed DNN-based speech enhancement algorithms c…
Incremental Averaging Method to Improve Graph-Based Time-Difference-of-Arrival Estimation
Klaus Brümann, Kouei Yamaoka, Nobutaka Ono +1
Estimating the position of a speech source based on time-differences-of-arrival (TDOAs) is often adversely affected by background noise and reverberation. A popular method to estim…
Soft-Constrained Spatially Selective Active Noise Control for Open-fitting Hearables
Tong Xiao, Reinhild Roden, Matthias Blau +1
Recent advances in spatially selective active noise control (SSANC) using multiple microphones have enabled hearables to suppress undesired noise while preserving desired speech fr…
Spatially Selective Active Noise Control for Open-fitting Hearables with Acausal Optimization
Tong Xiao, Simon Doclo
Recent advances in active noise control have enabled the development of hearables with spatial selectivity, which actively suppress undesired noise while preserving desired sound f…
Low-Complexity Own Voice Reconstruction for Hearables with an In-Ear Microphone
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Hearable devices, equipped with one or more microphones, are commonly used for speech communication. Here, we consider the scenario where a hearable is used to capture the user's o…
Speech-dependent Data Augmentation for Own Voice Reconstruction with Hearable Microphones in Noisy Environments
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Own voice pickup for hearables in noisy environments benefits from using both an outer and an in-ear microphone outside and inside the occluded ear. Due to environmental noise reco…
Deep low-latency joint speech transmission and enhancement over a gaussian channel
Mohammad Bokaei, Jesper Jensen, Simon Doclo +1
Ensuring intelligible speech communication for hearing assistive devices in low-latency scenarios presents significant challenges in terms of speech enhancement, coding and transmi…
Array Geometry-Robust Attention-Based Neural Beamformer for Moving Speakers
Marvin Tammen, Tsubasa Ochiai, Marc Delcroix +3
Although mask-based beamforming is a powerful speech enhancement approach, it often requires manual parameter tuning to handle moving speakers. Recently, this approach was augmente…
Effect of target signals and delays on spatially selective active noise control for open-fitting hearables
Tong Xiao, Simon Doclo
Spatially selective active noise control (ANC) hearables are designed to reduce unwanted noise from certain directions while preserving desired sounds from other directions. In pre…
Multi-Microphone Noise Data Augmentation for DNN-based Own Voice Reconstruction for Hearables in Noisy Environments
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Hearables with integrated microphones may offer communication benefits in noisy working environments, e.g. by transmitting the recorded own voice of the user. Systems aiming at rec…
Head Orientation Estimation with Distributed Microphones Using Speech Radiation Patterns
Kaspar Müller, Bilgesu Çakmak, Paul Didier +3
Determining the head orientation of a talker is not only beneficial for various speech signal processing applications, such as source localization or speech enhancement, but also f…
Modeling of Speech-dependent Own Voice Transfer Characteristics for Hearables with In-ear Microphones
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Many hearables contain an in-ear microphone, which may be used to capture the own voice of its user. However, due to the hearable occluding the ear canal, the in-ear microphone mos…
Speech-dependent Modeling of Own Voice Transfer Characteristics for In-ear Microphones in Hearables
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Many hearables contain an in-ear microphone, which may be used to capture the own voice of its user in noisy environments. Since the in-ear microphone mostly records body-conducted…