| 1. |
- Balázs, C., et al.
(författare)
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A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications
- 2021
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Ingår i: Journal of High Energy Physics (JHEP). - : Springer Nature. - 1126-6708 .- 1029-8479. ; 2021:5
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Tidskriftsartikel (refereegranskat)abstract
- Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.
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| 2. |
- Taal, Cees H., et al.
(författare)
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A Short-Time Objective Intelligibility Measure for Time-Frequency Weighted Noisy Speech
- 2010
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Konferensbidrag (refereegranskat)abstract
- Existing objective speech-intelligibility measures are suitable for several types of degradation, however, it turns out that they are less appropriate for methods where noisy speech is processed by a time-frequency (TF) weighting, e.g., noise reduction and speech separation. In this paper, we present an objective intelligibility measure, which shows high correlation (rho=0.95) with the intelligibility of both noisy, and TF-weighted noisy speech. The proposed method shows significantly better performance than three other, more sophisticated, objective measures. Furthermore, it is based on an intermediate intelligibility measure for short-time (approximately 400 ms) TF-regions, and uses a simple DFT-based TF-decomposition. In addition, a free Matlab implementation is provided.
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| 3. |
- Taal, Cees H., et al.
(författare)
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An Algorithm for Intelligibility Prediction of Time-Frequency Weighted Noisy Speech
- 2011
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Ingår i: IEEE Transactions on Audio, Speech, and Language Processing. - 1558-7916 .- 1558-7924. ; 19, s. 2125-2136
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Tidskriftsartikel (refereegranskat)abstract
- In the development process of noise-reduction algorithms, an objective machine-driven intelligibility measure which shows high correlation with speech intelligibility is of great interest. Besides reducing time and costs compared to real listening experiments, an objective intelligibility measure could also help provide answers on how to improve the intelligibility of noisy unprocessed speech. In this paper, a short-time objective intelligibility measure (STOI) is presented, which shows high correlation with the intelligibility of noisy and time-frequency weighted noisy speech (e.g., resulting from noise reduction) of three different listening experiments. In general, STOI showed better correlation with speech intelligibility compared to five other reference objective intelligibility models. In contrast to other conventional intelligibility models which tend to rely on global statistics across entire sentences, STOI is based on shorter time segments (386 ms). Experiments indeed show that it is beneficial to take segment lengths of this order into account. In addition, a free Matlab implementation is provided.
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| 4. |
- Taal, Cees. H., et al.
(författare)
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An evaluation of objective measures for intelligibility prediction of time-frequency weighted noisy speech
- 2011
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Ingår i: Journal of the Acoustical Society of America. - : Acoustical Society of America (ASA). - 0001-4966. ; 130, s. 3013-3027
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Tidskriftsartikel (refereegranskat)abstract
- Existing objective speech-intelligibility measures are suitable for several types of degradation, however, it turns out that they are less appropriate in cases where noisy speech is processed by a time-frequency weighting. To this end, an extensive evaluation is presented of objective measure for intelligibility prediction of noisy speech processed with a technique called ideal time frequency (TF) segregation. In total 17 measures are evaluated, including four advanced speech-intelligibility measures (CSII, CSTI, NSEC, DAU), the advanced speech-quality measure (PESQ), and several frame-based measures (e.g., SSNR). Furthermore, several additional measures are proposed. The study comprised a total number of 168 different TF-weightings, including unprocessed noisy speech. Out of all measures, the proposed frame-based measure MCC gave the best results (rho = 0.93). An additional experiment shows that the good performing measures in this study also show high correlation with the intelligibility of single-channel noise reduced speech.
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| 5. |
- Taal, Cees H., et al.
(författare)
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An Evaluation of Objective Quality Measures for Speech Intelligibility Prediction
- 2009
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Konferensbidrag (refereegranskat)abstract
- In this research various objective quality measures are evaluated in order to predict the intelligibility for a wide range of non-linearly processed speech signals and speech degraded by additive noise. The obtained results are compared with the prediction results of a more advanced perceptual-based model proposed by Dau et al. and an objective intelligibility measure, namely the coherence speech intelligibility index (cSII). These tests are performed in order to gain more knowledge between the link of speech-quality and speech-intelligibility and may help us to exploit the extensive research done into the field of speech-quality for speech-intelligibility. It is shown that cSII does not necessarily show better performance compared to conventional objective (speech)-quality measures. In general, the DAU-model is the only method with reasonable results for all processing conditions.
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| 6. |
- Taal, Cees H., et al.
(författare)
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Intelligibility Prediction of Single-Channel Noise-Reduced Speech
- 2010
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Konferensbidrag (refereegranskat)abstract
- In general, single-channel noise-reduction algorithms do not improve the speech intelligibility for normal-hearing listeners. A reliable objective intelligibility measure is therefore of great interest. It could be used for analysis and/or optimization of noise-reduction algorithms. For these applications it is important that the objective measure can correctly predict the difference in intelligibility before and after noise reduction. Typically, existing studies do not evaluate objective measures for this property. Twelve objective measures are evaluated in order to let them predict the intelligibility before and after noise reduction. Best performance was obtained with a recently developed intelligibility predictor called STOI. Modest results were obtained with WSS and NSEC. The remaining measures significantly overestimated the intelligibility of the noise-reduced speech.
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| 7. |
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