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Christopher Schymura

6 accepted papers

2021

Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domain

Julio Wissing, Benedikt T. Boenninghoff, Dorothea Kolossa, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita +3
ICASSP 2021accepted

Estimating the positions of multiple speakers can be helpful for tasks like automatic speech recognition or speaker diarization. Both applications benefit from a known speaker position when, for instance, applying beamforming or assigning unique speaker identities. Recently, several approaches utili…

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2020

A Dynamic Stream Weight Backprop Kalman Filter for Audiovisual Speaker Tracking

Christopher Schymura, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita, Tomohiro Nakatani, Shoko Araki +1
ICASSP 2020accepted

Audiovisual speaker tracking is an application that has been tackled by a wide range of classical approaches based on Gaussian filters, most notably the well-known Kalman filter. Recently, a specific Kalman filter implementation was proposed for this task, which incorporated dynamic stream weights t…

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2019

Learning Dynamic Stream Weights for Linear Dynamical Systems Using Natural Evolution Strategies

Christopher Schymura, Dorothea Kolossa
ICASSP 2019accepted

Multimodal data fusion is an important aspect of many object localization and tracking frameworks that rely on sensory observations from different sources. A prominent example is audiovisual speaker localization, where the incorporation of visual information has shown to benefit overall performance,…

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2018

Potential-Field-Based Active Exploration for Acoustic Simultaneous Localization and Mapping

Christopher Schymura, Dorothea Kolossa
ICASSP 2018accepted

This paper presents a novel framework for active exploration in the context of acoustic simultaneous localization and mapping (SLAM) using a microphone array mounted on a mobile robotic agent. Acoustic SLAM aims at building a map of acoustic sources present in the environment and simultaneously esti…

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2017

Improving audio-visual speech recognition using deep neural networks with dynamic stream reliability estimates

Hendrik Meutzner, Ning Ma, Robert M. Nickel, Christopher Schymura, Dorothea Kolossa
ICASSP 2017accepted

Audio-visual speech recognition is a promising approach to tackling the problem of reduced recognition rates under adverse acoustic conditions. However, finding an optimal mechanism for combining multi-modal information remains a challenging task. Various methods are applicable for integrating acous…

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2017

Monte Carlo exploration for active binaural localization

Christopher Schymura, Juan Diego Rios Grajales, Dorothea Kolossa
ICASSP 2017accepted

This study introduces a machine hearing system for robot audition, which enables a robotic agent to pro-actively minimize the uncertainty of sound source location estimates through motion. The proposed system is based on an active exploration approach, providing a means to model and predict effects…

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