2 citations · 4 across the 9 of their papers we have counts for
6 papers · 1 filter
Spatial Diarization for Meeting Transcription with Ad-Hoc Acoustic Sensor Networks
Tobias Gburrek, Joerg Schmalenstroeer, Reinhold Haeb-Umbach
We propose a diarization system, that estimates "who spoke when" based on spatial information, to be used as a front-end of a meeting transcription system running on the signals ga…
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network
Tobias Gburrek, Christoph Boeddeker, Thilo von Neumann +3
We propose a system that transcribes the conversation of a typical meeting scenario that is captured by a set of initially unsynchronized microphone arrays at unknown positions. It…
On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-varying Sampling Rate Offsets and Speaker Changes
Tobias Gburrek, Joerg Schmalenstroeer, Reinhold Haeb-Umbach
A wireless acoustic sensor network records audio signals with sampling time and sampling rate offsets between the audio streams, if the analog-digital converters (ADCs) of the netw…
Iterative Geometry Calibration from Distance Estimates for Wireless Acoustic Sensor Networks
Tobias Gburrek, Joerg Schmalenstroeer, Reinhold Haeb-Umbach
In this paper we present an approach to geometry calibration in wireless acoustic sensor networks, whose nodes are assumed to be equipped with a compact microphone array. The propo…
Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Networks
Tobias Gburrek, Joerg Schmalenstroeer, Andreas Brendel +2
We present an approach to deep neural network based (DNN-based) distance estimation in reverberant rooms for supporting geometry calibration tasks in wireless acoustic sensor netwo…
Statistical and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic Environments
Jens Heitkaemper, Joerg Schmalenstroeer, Reinhold Haeb-Umbach
Speech activity detection (SAD), which often rests on the fact that the noise is "more" stationary than speech, is particularly challenging in non-stationary environments, because…