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- Ahgren, Per, et al.
(författare)
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A study of doubletalk detection performance in the presence of acoustic echo path changes
- 2006
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Ingår i: IEEE transactions on consumer electronics. - Uppsala Univ, Dept Syst & Control, Informat Control, SE-75105 Uppsala, Sweden. Karlstad Univ, Dept Elect Engn, SE-65188 Karlstad, Sweden.. - 0098-3063 .- 1558-4127. ; 52:2, s. 515-522
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Tidskriftsartikel (refereegranskat)abstract
- An efficient and well-performing double-talk detection (DTD) algorithm is a vital part of a practically working acoustic echo canceller. However, recent algorithms are typically evaluated using a static time-invariant room acoustic impulse response, omitting a proper treatment of the case when the acoustic path is changing. In this work, we introduce a common framework to objectively evaluate how path changes affect the DTD performance. Via extensive numerical simulations, we conclude that the main factor in acoustic path changes affecting the DTD performance for some of the more common DTD algorithms is variations in the damping of the acoustic path.
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| 3. |
- Bergman, Erik, et al.
(författare)
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BERT based natural language processing for triage of adverse drug reaction reports shows close to human-level performance
- 2023
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Ingår i: PLOS Digital Health. - : Public Library of Science (PLoS). - 2767-3170. ; 2:12
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Tidskriftsartikel (refereegranskat)abstract
- Post-marketing reports of suspected adverse drug reactions are important for establishing the safety profile of a medicinal product. However, a high influx of reports poses a challenge for regulatory authorities as a delay in identification of previously unknown adverse drug reactions can potentially be harmful to patients. In this study, we use natural language processing (NLP) to predict whether a report is of serious nature based solely on the free-text fields and adverse event terms in the report, potentially allowing reports mislabelled at time of reporting to be detected and prioritized for assessment. We consider four different NLP models at various levels of complexity, bootstrap their train-validation data split to eliminate random effects in the performance estimates and conduct prospective testing to avoid the risk of data leakage. Using a Swedish BERT based language model, continued language pre-training and final classification training, we achieve close to human-level performance in this task. Model architectures based on less complex technical foundation such as bag-of-words approaches and LSTM neural networks trained with random initiation of weights appear to perform less well, likely due to the lack of robustness that a base of general language training provides.
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| 4. |
- Björk, Marcus, 1985-
(författare)
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Contributions to Signal Processing for MRI
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Magnetic Resonance Imaging (MRI) is an important diagnostic tool for imaging soft tissue without the use of ionizing radiation. Moreover, through advanced signal processing, MRI can provide more than just anatomical information, such as estimates of tissue-specific physical properties.Signal processing lies at the very core of the MRI process, which involves input design, information encoding, image reconstruction, and advanced filtering. Based on signal modeling and estimation, it is possible to further improve the images, reduce artifacts, mitigate noise, and obtain quantitative tissue information.In quantitative MRI, different physical quantities are estimated from a set of collected images. The optimization problems solved are typically nonlinear, and require intelligent and application-specific algorithms to avoid suboptimal local minima. This thesis presents several methods for efficiently solving different parameter estimation problems in MRI, such as multi-component T2 relaxometry, temporal phase correction of complex-valued data, and minimizing banding artifacts due to field inhomogeneity. The performance of the proposed algorithms is evaluated using both simulation and in-vivo data. The results show improvements over previous approaches, while maintaining a relatively low computational complexity. Using new and improved estimation methods enables better tissue characterization and diagnosis.Furthermore, a sequence design problem is treated, where the radio-frequency excitation is optimized to minimize image artifacts when using amplifiers of limited quality. In turn, obtaining higher fidelity images enables improved diagnosis, and can increase the estimation accuracy in quantitative MRI.
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| 5. |
- Christensen, M, et al.
(författare)
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Multi-pitch estimation
- 2008
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 88:4, s. 972-983
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we formulate the multi-pitch estimation problem and propose a number of methods to estimate the set of fundamental frequencies. The proposed methods, based on the nonlinear least-squares (NLS), Multiple Signal Classification (MUSIC) and the Capon principles, estimate the multiple fundamental frequencies via a number of one-dimensional searches. We also propose an iterative method based on the Expectation Maximization (EM) algorithm. The statistical properties of the methods are evaluated via Monte Carlo simulations for both the single- and multi-pitch cases.
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| 9. |
- Gudmundson, Erik, et al.
(författare)
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Blood velocity estimation using ultrasound and spectral iterative adaptive approaches
- 2011
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 91:5, s. 1275-1283
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes two novel iterative data-adaptive spectral estimation techniques for blood velocity estimation using medical ultrasound scanners. The techniques make no assumption on the sampling pattern of the emissions or the depth samples, allowing for duplex mode transmissions where B-mode images are interleaved with the Doppler emissions. Furthermore, the techniques are shown, using both simplified and more realistic Field II simulations as well as in vivo data, to outperform current state-of-the-art techniques, allowing for accurate estimation of the blood velocity spectrum using only 30% of the transmissions, thereby allowing for the examination of two separate vessel regions while retaining an adequate updating rate of the B-mode images. In addition, the proposed methods also allow for more flexible transmission patterns, as well as exhibit fewer spectral artifacts as compared to earlier techniques.
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| 10. |
- Gudmundson, Erik, et al.
(författare)
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Detection and Classification of Liquid Explosives Using NMR
- 2009
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Ingår i: 2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING. - 9781424423538 ; , s. 3053-3056, s. 3053-3056
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Konferensbidrag (refereegranskat)abstract
- In this work, we present a novel method for non-invasive identification of liquids, for instance to allow for the detection of liquid explosives at airports or border controls. The approach is based on a nuclear magnetic resonance technique with an inhomogeneous magnetic field, forming estimates of the liquid's spin-spin relaxation time, T(2), and diffusion constant, D, thereby allowing for a unique classification of the liquid. The proposed detectors are evaluated using both simulated and measured data sets.
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