Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Franz Pernkopf"'
Autor:
Jean Schoentgen, Martin Hagmüller, Franz Pernkopf, Philipp Aichinger, Berit Schneider-Stickler
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 26:330-341
Diplophonia is a type of pathological voice in which two fundamental frequencies ( $f_o$ ) are present simultaneously. Specialized audio analyzers that can handle up to two $f_o$ s in diplophonic voices are in their infancy. We propose the tracking o
Autor:
Franz Pernkopf, Wolfgang Roth
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 42(1)
We extend feed-forward neural networks with a Dirichlet process prior over the weight distribution. This enforces a sharing on the network weights, which can reduce the overall number of parameters drastically. We alternately sample from the posterio
Publikováno v:
ICASSP
In this paper, we present an optimal multi-channel Wiener filter, which consists of an eigenvector beamformer and a single-channel postfilter. We show that both components solely depend on a speech presence probability, which we learn using a deep ne
Autor:
Christina Leitner, Franz Pernkopf
Publikováno v:
SpringerPlus
In this paper, we apply kernel PCA for speech enhancement and derive pre-image iterations for speech enhancement. Both methods make use of a Gaussian kernel. The kernel variance serves as tuning parameter that has to be adapted according to the SNR a
Publikováno v:
ICASSP
While nonnegative matrix factorization (NMF) has successfully been applied for gain-robust multi-pitch detection, a method to track pitch values over time was not provided. We embed NMF-based pitch detection into a recently proposed pitch-tracking sy
Publikováno v:
ICASSP
We significantly improve the computational efficiency of a probabilistic approach for multiple pitch tracking. This method is based on a factorial hidden Markov model and two alternative interaction models for magnitude and log-magnitude spectra, res
Autor:
Franz Pernkopf, Christina Leitner
Publikováno v:
Advances in Nonlinear Speech Processing ISBN: 9783642250194
NOLISP
NOLISP
In this paper, we use kernel principal component analysis (kPCA) for speech enhancement. To synthesize the de-noised audio signal we rely on an iterative pre-image method. In order to gain better understanding about the pre-image step we performed ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3cddfc9e119721dd25285fc9653004fe
https://doi.org/10.1007/978-3-642-25020-0_26
https://doi.org/10.1007/978-3-642-25020-0_26
Publikováno v:
ICASSP
We present a simple and efficient feature modeling approach for tracking the pitch of two speakers speaking simultaneously. We model the spectrogram features of single speakers using Gaussian mixture models in combination with the minimum description
Autor:
Michael Stark, Franz Pernkopf
Publikováno v:
ICASSP
We present a new source-filter based method to separate two speakers talking simultaneously at equal level mixed into a single sensor. First, the relation between the spectral whitened mixture and the speakers excitation signals is analyzed. Therefor
Publikováno v:
CBMI
In this paper, a new representation for acoustic source indexing in a multi-source environment is introduced. Each source is represented by a two-dimensional Gaussian-like probability distribution as a function of pitch and direction-of-arrival (DoA)