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Representation models in single channel source separation 40

Representation models in single channel source separation

引用

40th IEEE International Conference on Acoustics, speech, and signal processing, ICASSP 2015

作者： Zohrer, Matthias Pernkopf, Franz Signal Processing and Speech Communication Lab Graz University of Technology Austria

ISBN: (纸本)9781467369978

Model-based single-channel source separation (SCSS) is an ill-posed problem requiring source-specific prior knowledge. In this paper, we use representation learning and compare general stochastic networks (GSNs), Gauss Bernoulli restricted Boltzmann machines (GBRBMs), conditional Gauss Bernoulli restricted Boltzmann machines (CGBRBMs), and higher order contractive autoencoders (HCAEs) for modeling the source-specific knowledge. In particular, these models learn a mapping from speech mixture spectrogram representations to single-source spectrogram representations, i.e. we apply them as filter for the speech mixture. In the test case, the individual source spectrograms of both models are inferred and the softmask for re-synthesis of the time signals is determined thereof. We evaluate the deep architectures on data of the 2nd CHiME speech separation challenge and provide results for a speaker dependent, a speaker independent, a matched noise condition and an unmatched noise condition task. Our experiments show the best PESQ and overall perceptual score on average for GSNs in all four tasks. © 2015 IEEE.

关键词： deep neural networks general stochastic network representation models single channel source separation

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Comparison between silence substitution and packet repetition for real-time speech communications

Comparison between silence substitution and packet repetitio...

引用

Measurement of speech and Audio Quality in Networks, MESAQIN 2005

作者： Ehsan, M. Sarwar Kubin, G. Signal Processing and Speech Communication Lab Graz University of Technology Austria

Real-time speech communication over packet switched networks requires low delay packet loss concealment (PLC) methods. There are several PLC methods used in IP telephony to cope with packet losses. Two commonly used methods are silence substitution and packet (waveform) repetition. We compare these methods according to the rate distortion criterion by introducing a penalty for packet (waveform) repetition. This analysis allows us for fair comparison between the two methods. We also compare the results with that of ITU-T's E-model and find them to be in agreement.

关键词： speech communication

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On speech quality estimation of phase-aware single-channel speech enhancement 40

On speech quality estimation of phase-aware single-channel s...

引用

40th IEEE International Conference on Acoustics, speech, and signal processing, ICASSP 2015

作者： Gaich, Andreas Mowlaee, Pejman Signal Processing and Speech Communication Lab Graz University of Technology Austria

ISBN: (纸本)9781467369978

To approximate the speech quality of a given speech enhancement system, most of the existing instrumental metrics rely on the calculation of a distortion metric defined between the clean reference signal and the enhanced signal in the spectral amplitude domain. Several recent studies have demonstrated the effectiveness of employing a phase modification stage in single-channel speech enhancement showing positive impact brought by modifying both amplitude and phase in contrast to the conventional methods where the noisy spectral amplitude is only modified and noisy phase is used for signal reconstruction. In this work we present two contributions;First we study the reliability of the existing instrumental metrics for performance evaluation of phase-aware methods, and second we propose novel phase-aware instrumental metrics and evaluate their reliability in terms of predicting the perceived quality achieved by the phase-aware methods. Our objective and subjective evaluations demonstrate that PESQ and the proposed phase deviation metric perform as reliable speech quality estimators following the subjective results. © 2015 IEEE.

关键词： perceived speech quality Phase estimation phase-aware speech enhancement subjective listening

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A Matlab-based magnitude response game for DSP education

A Matlab-based magnitude response game for DSP education

引用

2014 IEEE International Conference on Acoustics, speech, and signal processing, ICASSP 2014

作者： Casapicola, Peter Polzl, Markus Geiger, Bernhard C. Signal Processing and Speech Communication Lab Graz University of Technology Austria

ISBN: (纸本)9781479928927

We present a Matlab-based game, teaching the interplay between the pole-zero chart of a linear filter and its magnitude response. The estimation error, which acts as a game score, is based on concepts undergraduate students learn during elementary signal processing courses at our university. The game is accompanied by an online database collecting the players' results and admitting a statistical analysis thereof. © 2014 IEEE.

关键词： Teaching

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Comparison of SRP-PHAT and Multiband-PoPi algorithms for speaker localization using particle filters

Comparison of SRP-PHAT and Multiband-PoPi algorithms for spe...

引用

13th International Conference on Digital Audio Effects, DAFx 2010

作者： Habib, Tania Romsdorfer, Harald Signal Processing and Speech Communication Lab Graz University of Technology Graz Austria

ISBN: (纸本)9783200019409

The task of localizing single and multiple concurrent speakers in a reverberant environment with background noise poses several problems. One of the major problems is the severe corruption of the frame-wise localization estimates. To improve the overall localization accuracy, we propose a particle filter based tracking algorithm using the recently proposed Multiband Joint Position-Pitch (M-PoPi) localization algorithm as a frame wise likelihood estimate. To prove the performance of our approach, we tested it on real-world recordings of seven different speakers and of up to three concurrent speakers. We compared our new approach to the well-known SRP-PHAT algorithm as frame-wise likelihood estimates. Finally, we compared both particle filter based tracking algorithms with their frame-wise localization algorithms. The M-PoPi based particle filter tracking algorithm outperforms the SRPPHAT based particle filter tracking algorithm. The comparison with their frame wise localization algorithms shows that this improved performance stems from the more robust M-PoPi frame wise localization estimate.

关键词： Monte Carlo methods

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Harmonic phase estimation in single-channel speech enhancement using von mises distribution and prior SNR 40

Harmonic phase estimation in single-channel speech enhanceme...

引用

40th IEEE International Conference on Acoustics, speech, and signal processing, ICASSP 2015

作者： Kulmer, Josef Mowlaee, Pejman Signal Processing and Speech Communication Lab Graz University of Technology Graz Austria

ISBN: (纸本)9781467369978

In single-channel speech enhancement the spectral amplitude of the noisy signal is often modified while the noisy spectral phase is directly employed for signal reconstruction. Recently, additional improvement in speech enhancement performance has been reported when the noisy phase is modified. In this work, we propose a Bayesian estimator for phase of harmonics given the noisy speech. The proposed estimator relies on the fundamental frequency and the signal-to-noise ratio at harmonics. Throughout our experiments, we evaluate the performance of the proposed phase enhancement in comparison with the noisy phase, a benchmark and the clean phase as the upper-bound. The proposed method leads to joint improvement in quality and intelligibility at different SNRs and noise types. © 2015 IEEE.

关键词： Bayesian estimation harmonic model Phase estimation speech enhancement Von Mises distribution

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Sparse nonnegative matrix factorization using 0-constraints

Sparse nonnegative matrix factorization using 0-constraints

引用

2010 IEEE 20th International Workshop on Machine Learning for signal processing, MLSP 2010

作者： Peharz, Robert Stark, Michael Pernkopf, Franz Signal Processing and Speech Communication Lab. University of Technology Graz Austria

ISBN: (纸本)9781424478774

Although nonnegative matrix factorization (NMF) favors a part-based and sparse representation of its input, there is no guarantee for this behavior. Several extensions to NMF have been proposed in order to introduce sparseness via the 1-norm, while little work is done using the more natural sparseness measure, the 0-pseudo-norm. In this work we propose two NMF algorithms with 0-sparseness constraints on the bases and the coefficient matrices, respectively. We show that classic NMF [1] is a suited tool for 0-sparse NMF algorithms, due to a property we call sparseness maintenance. We apply our algorithms to synthetic and real-world data and compare our results to sparse NMF [2] and nonnegative KSVD [3]. ©2010 IEEE.

关键词： Matrix algebra

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Combining multiband joint position-pitch algorithm and particle filters for speaker localization

Combining multiband joint position-pitch algorithm and parti...

引用

IEEE Sensor Array and Multichannel signal processing Workshop

作者： Habib, Tania Romsdorfer, Harald Signal Processing and Speech Communication Lab. Graz University of Technology Austria

ISBN: (纸本)9781424489770

We present a combination of the multiband joint positionpitch (M-PoPi) estimation algorithm with the particle filtering framework to enhance the localization accuracy when tracking multiple concurrent speakers. A new likelihood function derived from the M-PoPi algorithm is proposed for the particle filter framework. The performance of the particle filter based tracker is compared with the M-PoPi algorithm. The proposed framework improves localization accuracy for all cases ranging from single upto three concurrent speakers. © 2010 IEEE.

关键词： Monte Carlo methods

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Lung Sound Classification Using Snapshot Ensemble of Convolutional Neural Networks 42

Lung Sound Classification Using Snapshot Ensemble of Convolu...

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42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020

作者： Nguyen, Truc Pernkopf, Franz Graz University of Technology Signal Processing and Speech Communication Lab GrazA-8010 Austria

ISBN: (纸本)9781728119908

We propose a robust and efficient lung sound classification system using a snapshot ensemble of convolutional neural networks (CNNs). A robust CNN architecture is used to extract high-level features from log mel spectrograms. The CNN architecture is trained on a cosine cycle learning rate schedule. Capturing the best model of each training cycle allows to obtain multiple models settled on various local optima from cycle to cycle at the cost of training a single mode. Therefore, the snapshot ensemble boosts performance of the proposed system while keeping the drawback of expensive training of ensembles moderate. To deal with the class-imbalance of the dataset, temporal stretching and vocal tract length perturbation (VTLP) for data augmentation and the focal loss objective are used. Empirically, our system outperforms state-of-the-art systems for the prediction task of four classes (normal, crackles, wheezes, and both crackles and wheezes) and two classes (normal and abnormal (i.e. crackles, wheezes, and both crackles and wheezes)) and achieves 78.4% and 83.7% ICBHI specific micro-averaged accuracy, respectively. The average accuracy is repeated on ten random splittings of 80% training and 20% testing data using the ICBHI 2017 dataset of respiratory cycles. © 2020 IEEE.

关键词： Convolutional neural networks

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Iterative harmonic speech enhancement

Iterative harmonic speech enhancement

引用

12. ITG-Fachtagung Sprachkommunikation - 12th ITG Conference on speech communication

作者： Stahl, Johannes Mowlaee, Pejman Signal Processing and Speech Communication Lab. Graz University of Technology Graz8010 Austria

ISBN: (纸本)9783800742752

Several iterative approaches have been proposed for speech enhancement. This work reviews these methods and further presents a novel iterative estimation scheme to jointly estimate the harmonic parameters, i.e., amplitude, frequency and phase of a speech signal observed in noise. The potential of the proposed iterative method in terms of harmonic parameter estimation is analyzed on synthetic harmonic signals. Further, by applying our proposed method on noise-corrupted speech files at different signal-to-noise ratios, we demonstrate its effectiveness in improving in-strumentally predicted speech intelligibility and perceived speech quality. © 2016 VDE VERLAG GMBH.

关键词： speech enhancement

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