@article{45575, abstract = {{In this work, we discuss the possibility of improving charge neutralization in near ambient pressure X-ray photoelectron spectroscopy by co-irradiating the sample with He I photons of 21.2 eV. This UV-enhanced neutralization of charges is a variation of the so-called environmental charge compensation, which uses the electrons produced by the photoionization of the ambient gas to neutralize the positive charges built at the sample surface. Adding an additional ionization source generates more charges at the sample but also larger amounts of electrons available for neutralization. The final surface charge equilibrium depends on different aspects of the experiment, such as the sample composition and geometry, the total ionization cross sections of the gas compared to the surface materials, the gas used, the luminosity and spot size of the sources used for photoionization, and the energy of the electrons present in the gas phase. Here we illustrate the efficiency of the UV-enhanced neutralization using three different dielectric samples with different geometries (a porous SiO2 monolith with an irregular surface, a flat mica sample, and a thin SiO2 film deposited onto a Si substrate), different X-ray spot sizes, and two different gases (N2 and Ar). The effect of biasing on the efficiency of the sample surface to attract electrons produced in the gas phase is also discussed.}}, author = {{Arcos, Teresa de los and Müller, Hendrik and Weinberger, Christian and Grundmeier, Guido}}, issn = {{0368-2048}}, journal = {{Journal of Electron Spectroscopy and Related Phenomena}}, keywords = {{XPS, Near ambient pressure, Environmental charge compensation, UV}}, number = {{264}}, publisher = {{Elsevier}}, title = {{{UV-enhanced environmental charge compensation in near ambient pressure XPS}}}, doi = {{10.1016/j.elspec.2023.147317}}, volume = {{264}}, year = {{2023}}, } @article{20688, abstract = {{We offer the first empirical analysis connecting the timing of general partner (GP) compensation to private equity fund performance. Using detailed information on limited partnership agreements between private equity limited and general partners, we find that “GP-friendly” contracts—agreements that pay general partners on a deal-by-deal basis instead of withholding carried interest until a benchmark return has been earned—are associated with higher returns, both gross and net of fees. This is robust to measures of performance persistence, time period effects, and other contract terms and is related to exit-timing incentives. Timing practices balance GP incentives against limited partner downside protection.}}, author = {{Hüther, Niklas and Robinson, David T. and Sievers, Sönke and Hartmann-Wendels, Thomas}}, issn = {{0025-1909}}, journal = {{Management Science (VHB-JOURQUAL 4 Ranking A+)}}, keywords = {{venture capital, compensation, private equity, VC partnership, pay-performance relation}}, number = {{4}}, pages = {{1756--1782}}, title = {{{Paying for Performance in Private Equity: Evidence from Venture Capital Partnerships}}}, doi = {{10.1287/mnsc.2018.3274}}, volume = {{66}}, year = {{2019}}, } @inbook{2322, abstract = {{The vision of On-The-Fly Computing is an automatic composition of existing software services. Based on natural language software descriptions, end users will receive compositions tailored to their needs. For this reason, the quality of the initial software service description strongly determines whether a software composition really meets the expectations of end users. In this paper, we expose open NLP challenges needed to be faced for service composition in On-The-Fly Computing.}}, author = {{Bäumer, Frederik Simon and Geierhos, Michaela}}, booktitle = {{Proceedings of the 23rd International Conference on Natural Language and Information Systems}}, editor = {{Silberztein, Max and Atigui, Faten and Kornyshova, Elena and Métais, Elisabeth and Meziane, Farid }}, isbn = {{978-3-319-91946-1}}, keywords = {{Requirements Extraction, Temporal Reordering of Software Functions, Inaccuracy Compensation}}, location = {{Paris, France}}, pages = {{509--513}}, publisher = {{Springer}}, title = {{{How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges}}}, doi = {{10.1007/978-3-319-91947-8_53}}, volume = {{10859}}, year = {{2018}}, } @article{5185, abstract = {{We offer the first empirical analysis connecting the timing of general partner (GP) compensation to private equity fund performance. Using detailed information on limited partnership agreements between private equity limited and general partners, we find that "GP-friendly" contracts - agreements that pay general partners on a deal-by-deal basis instead of withholding carried interest until a benchmark return has been earned - are associated with higher returns, both gross and net of fees. This is robust to measures of performance persistence, time period effects, and other contract terms, and is related to exit-timing incentives. Timing practices balance GP incentives against limited partner downside protection. }}, author = {{Hüther, Niklas and Robinson, David and Sievers, Sönke and Hartmann-Wendels, Thomas}}, journal = {{SSRN Electronic Journal}}, keywords = {{venture capital, compensation, private equity, VC partnership, pay-performance relation}}, title = {{{Paying for Performance in Private Equity: Evidence from VC Partnerships}}}, doi = {{10.2139/ssrn.3087320}}, year = {{2017}}, } @article{3376, abstract = {{Employing compensation data provided by 63 banks from 16 European countries for the period from 2000 to 2010 this paper empirically investigates the impact of excess variable compensation on bank risk. As a main finding, we provide evidence for a risk-increasing impact of excess variable pay for both executive variable cash-based and variable equity-based compensation. This baseline finding holds under various robustness checks, in particular when controlling for likely reverse causality between bank risk and variable compensation by employing Granger-causality tests and instrumental variable regressions. In addition, results from a large number of sensitivity analyses including board and banking characteristics as well as the financial crisis period and the quality of a country's regulatory framework provide further important implications for banking regulators and politicians in Europe.}}, author = {{Uhde, André}}, journal = {{The Quarterly Review of Economics and Finance}}, keywords = {{Banking, Executive compensation, Risk-taking, Financial stability}}, number = {{5}}, pages = {{12--28}}, publisher = {{Elsevier}}, title = {{{Risk-taking incentives through excess variable compensation: Evidence from European banks}}}, doi = {{https://doi.org/10.1016/j.qref.2015.11.009}}, volume = {{60}}, year = {{2016}}, } @article{11861, abstract = {{In this contribution we present a theoretical and experimental investigation into the effects of reverberation and noise on features in the logarithmic mel power spectral domain, an intermediate stage in the computation of the mel frequency cepstral coefficients, prevalent in automatic speech recognition (ASR). Gaining insight into the complex interaction between clean speech, noise, and noisy reverberant speech features is essential for any ASR system to be robust against noise and reverberation present in distant microphone input signals. The findings are gathered in a probabilistic formulation of an observation model which may be used in model-based feature compensation schemes. The proposed observation model extends previous models in three major directions: First, the contribution of additive background noise to the observation error is explicitly taken into account. Second, an energy compensation constant is introduced which ensures an unbiased estimate of the reverberant speech features, and, third, a recursive variant of the observation model is developed resulting in reduced computational complexity when used in model-based feature compensation. The experimental section is used to evaluate the accuracy of the model and to describe how its parameters can be determined from test data.}}, author = {{Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}}, issn = {{2329-9290}}, journal = {{IEEE/ACM Transactions on Audio, Speech, and Language Processing}}, keywords = {{computational complexity, reverberation, speech recognition, automatic speech recognition, background noise, clean speech, computational complexity, energy compensation, logarithmic mel power spectral domain, mel frequency cepstral coefficients, microphone input signals, model-based feature compensation schemes, noisy reverberant speech automatic recognition, noisy reverberant speech features, reverberation, Atmospheric modeling, Computational modeling, Noise, Noise measurement, Reverberation, Speech, Vectors, Model-based feature compensation, observation model for reverberant and noisy speech, recursive observation model, robust automatic speech recognition}}, number = {{1}}, pages = {{95--109}}, title = {{{A New Observation Model in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech}}}, doi = {{10.1109/TASLP.2013.2285480}}, volume = {{22}}, year = {{2014}}, } @article{11867, abstract = {{New waves of consumer-centric applications, such as voice search and voice interaction with mobile devices and home entertainment systems, increasingly require automatic speech recognition (ASR) to be robust to the full range of real-world noise and other acoustic distorting conditions. Despite its practical importance, however, the inherent links between and distinctions among the myriad of methods for noise-robust ASR have yet to be carefully studied in order to advance the field further. To this end, it is critical to establish a solid, consistent, and common mathematical foundation for noise-robust ASR, which is lacking at present. This article is intended to fill this gap and to provide a thorough overview of modern noise-robust techniques for ASR developed over the past 30 years. We emphasize methods that are proven to be successful and that are likely to sustain or expand their future applicability. We distill key insights from our comprehensive overview in this field and take a fresh look at a few old problems, which nevertheless are still highly relevant today. Specifically, we have analyzed and categorized a wide range of noise-robust techniques using five different criteria: 1) feature-domain vs. model-domain processing, 2) the use of prior knowledge about the acoustic environment distortion, 3) the use of explicit environment-distortion models, 4) deterministic vs. uncertainty processing, and 5) the use of acoustic models trained jointly with the same feature enhancement or model adaptation process used in the testing stage. With this taxonomy-oriented review, we equip the reader with the insight to choose among techniques and with the awareness of the performance-complexity tradeoffs. The pros and cons of using different noise-robust ASR techniques in practical application scenarios are provided as a guide to interested practitioners. The current challenges and future research directions in this field is also carefully analyzed.}}, author = {{Li, Jinyu and Deng, Li and Gong, Yifan and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech and Language Processing}}, keywords = {{Speech recognition, compensation, distortion modeling, joint model training, noise, robustness, uncertainty processing}}, number = {{4}}, pages = {{745--777}}, title = {{{An Overview of Noise-Robust Automatic Speech Recognition}}}, doi = {{10.1109/TASLP.2014.2304637}}, volume = {{22}}, year = {{2014}}, } @article{11862, abstract = {{In this contribution we extend a previously proposed Bayesian approach for the enhancement of reverberant logarithmic mel power spectral coefficients for robust automatic speech recognition to the additional compensation of background noise. A recently proposed observation model is employed whose time-variant observation error statistics are obtained as a side product of the inference of the a posteriori probability density function of the clean speech feature vectors. Further a reduction of the computational effort and the memory requirements are achieved by using a recursive formulation of the observation model. The performance of the proposed algorithms is first experimentally studied on a connected digits recognition task with artificially created noisy reverberant data. It is shown that the use of the time-variant observation error model leads to a significant error rate reduction at low signal-to-noise ratios compared to a time-invariant model. Further experiments were conducted on a 5000 word task recorded in a reverberant and noisy environment. A significant word error rate reduction was obtained demonstrating the effectiveness of the approach on real-world data.}}, author = {{Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{Bayes methods, compensation, error statistics, reverberation, speech recognition, Bayesian feature enhancement, background noise, clean speech feature vectors, compensation, connected digits recognition task, error statistics, memory requirements, noisy reverberant data, posteriori probability density function, recursive formulation, reverberant logarithmic mel power spectral coefficients, robust automatic speech recognition, signal-to-noise ratios, time-variant observation, word error rate reduction, Robust automatic speech recognition, model-based Bayesian feature enhancement, observation model for reverberant and noisy speech, recursive observation model}}, number = {{8}}, pages = {{1640--1652}}, title = {{{Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition}}}, doi = {{10.1109/TASL.2013.2258013}}, volume = {{21}}, year = {{2013}}, } @inproceedings{11824, abstract = {{Soft-feature based speech recognition, which is an example of uncertainty decoding, has been proven to be a robust error mitigation method for distributed speech recognition over wireless channels exhibiting bit errors. In this paper we extend this concept to packet-oriented transmissions. The a posteriori probability density function of the lost feature vector, given the closest received neighbours, is computed. In the experiments, the nearest frame repetition, which is shown to be equivalent to the MAP estimate, outperforms the MMSE estimate for long bursts. Taking the variance into account at the speech recognition stage results in superior performance compared to classical schemes using point estimates. A computationally and memory efficient implementation of the proposed packet loss compensation scheme based on table lookup is presented}}, author = {{Ion, Valentin and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)}}, keywords = {{distributed speech recognition, least mean squares methods, MAP estimate, maximum likelihood estimation, MMSE estimate, packet loss compensation scheme, packet switched communication, posteriori probability density function, robust error mitigation method, soft-features, speech recognition, table lookup, voice communication, wireless channels}}, pages = {{I}}, title = {{{An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features}}}, doi = {{10.1109/ICASSP.2006.1659984}}, volume = {{1}}, year = {{2006}}, }