Zobrazeno 1 - 10
of 296
pro vyhledávání: '"F, Hauth"'
Publikováno v:
Technical Innovations & Patient Support in Radiation Oncology, Vol 22, Iss , Pp 16-21 (2022)
Background: In radiotherapy the timely identification of patients needing intervention and supportive care due to side effects is an important task especially in the outpatient setting. Activity trackers as an increasingly used lifestyle device may e
Externí odkaz:
https://doaj.org/article/3767128e397649fbb6c48fe723f086e1
Autor:
Christopher F. Hauth, Thomas Brand
Publikováno v:
Trends in Hearing, Vol 22 (2018)
In studies investigating binaural processing in human listeners, relatively long and task-dependent time constants of a binaural window ranging from 10 ms to 250 ms have been observed. Such time constants are often thought to reflect “binaural slug
Externí odkaz:
https://doaj.org/article/25e59f50e04745a094b6bb9472b0d837
Autor:
Jana Roßbach, Rainer Huber, Saskia Röttges, Christopher F. Hauth, Thomas Biberger, Thomas Brand, Bernd T. Meyer, Jan Rennies
Publikováno v:
Interspeech 2022.
Speech perception is strongly affected by noise and reverberation in the listening room, and binaural processing can substantially facilitate speech perception in conditions when target speech and maskers originate from different directions. Most stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::325159f50f6450ad918f21c652cca98a
https://publica.fraunhofer.de/handle/publica/427602
https://publica.fraunhofer.de/handle/publica/427602
Akademický článek
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Publikováno v:
Forum. 37:59-61
Publikováno v:
Technical innovationspatient support in radiation oncology. 22
In radiotherapy the timely identification of patients needing intervention and supportive care due to side effects is an important task especially in the outpatient setting. Activity trackers as an increasingly used lifestyle device may enable physic
Publikováno v:
ICASSP
In this study, we explore an approach for modeling speech intelligibility in spatial acoustic scenes. To this end, we combine a non-intrusive binaural frontend with a deep neural network (DNN) borrowed from a standard automatic speech recognition (AS
Publikováno v:
Trends in Hearing
The equalization cancellation model is often used to predict the binaural masking level difference. Previously its application to speech in noise has required separate knowledge about the speech and noise signals to maximize the signal-to-noise ratio
Akademický článek
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