J
Joerg Schmalenstroeer
Researcher at University of Paderborn
Publications - 48
Citations - 494
Joerg Schmalenstroeer is an academic researcher from University of Paderborn. The author has contributed to research in topics: Microphone & Computer science. The author has an hindex of 11, co-authored 44 publications receiving 408 citations.
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Proceedings ArticleDOI
Front-end processing for the CHiME-5 dinner party scenario
Christoph Boeddeker,Jens Heitkaemper,Joerg Schmalenstroeer,Lukas Drude,Jahn Heymann,Reinhold Haeb-Umbach +5 more
TL;DR: This contribution presents a speech enhancement system for the CHiME-5 Dinner Party Scenario that employs multi-channel linear time-variant filtering and achieves its gains without the use of a neural network.
Journal ArticleDOI
Online Diarization of Streaming Audio-Visual Data for Smart Environments
TL;DR: A system for joint temporal segmentation, speaker localization, and identification is presented, supported by face identification from video data obtained from a steerable camera, which describes the vision of terminal-less, session-less and multi-modal telecommunication with remote partners.
Proceedings ArticleDOI
Smartphone-based sensor fusion for improved vehicular navigation
TL;DR: A system for car navigation by fusing sensor data on an Android smartphone that is able to maintain higher positioning accuracy during GPS dropouts, thus improving the availability and reliability, compared to GPS-only solutions.
Proceedings ArticleDOI
DOA-based microphone array postion self-calibration using circular statistics
TL;DR: The proposed calibration algorithm is derived from a maximum-likelihood approach employing circular statistics, and since a sensor node consists of a microphone array with known intra-array geometry, is able to obtain an absolute geometry estimate, including angles and distances.
Journal ArticleDOI
A combined hardware-software approach for acoustic sensor network synchronization
TL;DR: An approach for synchronizing a wireless acoustic sensor network using a two-stage procedure employing a Kalman filter with a dedicated observation error model and a gossiping algorithm which estimates the average clock frequency and phase of the sensor nodes.