Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Bernd Edler"'
Autor:
Michael Schoeffler, Sarah Bartoschek, Fabian-Robert Stöter, Marlene Roess, Susanne Westphal, Bernd Edler, Jürgen Herre
Publikováno v:
Journal of Open Research Software, Vol 6, Iss 1 (2018)
For a long time, many popular listening test methods, such as ITU-R BS.1534 (MUSHRA), could not be carried out as web-based listening tests, since established web standards did not support all required audio processing features. With the standardizat
Externí odkaz:
https://doaj.org/article/926e4c9b187d4668b0884b385438a5ec
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2009 (2009)
In contemporary cochlear implant systems, the audio signal is decomposed into different frequency bands, each assigned to one electrode. Thus, pitch perception is limited by the number of physical electrodes implanted into the cochlea and by the wide
Externí odkaz:
https://doaj.org/article/36faeaf071bc43b8bfaa9500bb0d0c68
Publikováno v:
AudioMostly 2022.
Autor:
Bernd Edler, Ning Guo
Publikováno v:
IEEE Signal Processing Letters. 28:1185-1189
In this paper we propose a long-term prediction method for low delay transform domain general audio coders. This Frequency Domain Joint Harmonics Prediction (FDJHP) method operates directly in the Modified Discrete Cosine Transform (MDCT) domain and
Frequency domain processing, and in particular the use of Modified Discrete Cosine Transform (MDCT), is the most widespread approach to audio coding. However, at low bitrates, audio quality, especially for speech, degrades drastically due to the lack
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99f8e0f458d78964bc60cbc01063a49e
Publikováno v:
Interspeech 2021.
This paper describes a hands-on comparison on using state-of-the-art music source separation deep neural networks (DNNs) before and after task-specific fine-tuning for separating speech content from non-speech content in broadcast audio (i.e., dialog
Autor:
Martin Strauss, Bernd Edler
Publikováno v:
ICASSP
Speech enhancement involves the distinction of a target speech signal from an intrusive background. Although generative approaches using Variational Autoencoders or Generative Adversarial Networks (GANs) have increasingly been used in recent years, n
Publikováno v:
2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS).
The possible fields of application for small sensor nodes are tremendous and still growing fast. Concepts like the Internet of Things (IoT), Smart City or Industry 4.0 adopt wireless sensor networks for environmental interaction or metering purposes.
Autor:
Bernd Edler, Konstantin Schmidt
Publikováno v:
EUSIPCO
A blind bandwidth extension is presented which improves the perceived quality of 4 kHz speech by artificially extending the speech’s frequency range to 8 kHz. Based on the source-filter model of the human speech production, the speech signal is dec
Autor:
Bernd Edler, Nils Werner
Publikováno v:
ICASSP
In this paper, we investigate the coding efficiency of perceptual coding using an adaptive non-uniform orthogonal filter-bank based on MDCT analysis/synthesis and time domain aliasing reduction. We compare its performance to a system using a traditio