Non-Linear and Non-Conventional Speech Processing: Alternative Techniques

This special issue aims to cover some problems related to non-linear and nonconventional speech processing. The origin of this volume is in the ISCA Tutorial and Research Workshop on Non-Linear Speech Processing, NOLISP’09, held at the Universitat de Vic (Catalonia, Spain) on June 25–27, 2009. The series of NOLISP workshops started in 2003 has become a biannual event whose aim is to discuss alternative techniques for speech processing that, in a sense, do not fit into mainstream approaches. A selected choice of papers based on the presentations delivered at NOLISP’09 has given rise to this issue of Cognitive Computation.

A Fast Gradient Approximation for Nonlinear Blind Signal Processing

When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation), complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing, spike signals deconvolution or microarray data analysis. In this paper, we propose a simple method to reduce computational time for the inversion of Wiener systems or the separation of post-nonlinear mixtures, by using a linear approximation in a minimum mutual information algorithm. Simulation results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. On the other hand, cubic spline interpolation also obtains similar good results, but due to its intrinsic complexity, the global algorithm is much more slow and hence not useful for our purpose.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Assessing the impact of high-pressure processing on selected physical and biochemical attributes of white cabbage (Brassica oleracea L. var. capitata alba)

The aim of this study was to investigate the effect of combined pressure/temperature treatments (200, 400 and 600 MPa, at 20 and 40 °C) on key physical and chemical characteristics of white cabbage (Brassica oleracea L. var. capitata alba). Thermal treatment (blanching) was also investigated and compared with high-pressure processing (HPP). HPP at 400 MPa and 20–40 °C caused significantly larger colour changes compared to any other pressure or thermal treatment. All pressure treatments induced a softening effect, whereas blanching did not significantly alter texture. Both blanching and pressure treatments resulted in a reduction in the levels of ascorbic acid, effect that was less pronounced for blanching and HPP at 600 MPa and 20–40 °C. HPP at 600 MPa resulted in significantly higher total phenol content, total antioxidant capacity and total isothiocyanate content compared to blanching. In summary, the colour and texture of white cabbage were better preserved by blanching. However, HPP at 600 MPa resulted in significantly higher levels of phytochemical compounds. The results of this study suggest that HPP may represent an attractive technology to process vegetable-based food products that better maintains important aspects related to the content of health-promoting compounds. This may be of particular relevance to the food industry sector involved in the development of convenient novel food products with excellent functional properties

The underestimation of compliance to direct help requests explained by adaptive sampling

Helping behavior is any intentional behavior that benefits another living being or group (Hogg & Vaughan, 2010). People tend to underestimate the probability that others will comply with their direct requests for help (Flynn & Lake, 2008). This implies that when they need help, they will assess the probability of getting it (De Paulo, 1982, cited in Flynn & Lake, 2008) and then they will tend to estimate one that is actually lower than the real chance, so they may not even consider worth asking for it. Existing explanations for this phenomenon attribute it to a mistaken cost computation by the help seeker, who will emphasize the instrumental cost of “saying yes”, ignoring that the potential helper also needs to take into account the social cost of saying “no”. And the truth is that, especially in face-to-face interactions, the discomfort caused by refusing to help can be very high. In short, help seekers tend to fail to realize that it might be more costly to refuse to comply with a help request rather than accepting. A similar effect has been observed when estimating trustworthiness of people. Fetchenhauer and Dunning (2010) showed that people also tend to underestimate it. This bias is reduced when, instead of asymmetric feedback (getting feedback only when deciding to trust the other person), symmetric feedback (always given) was provided. This cause could as well be applicable to help seeking as people only receive feedback when they actually make their request but not otherwise. Fazio, Shook, and Eiser (2004) studied something that could be reinforcing these outcomes: Learning asymmetries. By means of a computer game called BeanFest, they showed that people learn better about negatively valenced objects (beans in this case) than about positively valenced ones. This learning asymmetry esteemed from “information gain being contingent on approach behavior” (p. 293), which could be identified with what Fetchenhauer and Dunning mention as ‘asymmetric feedback’, and hence also with help requests. Fazio et al. also found a generalization asymmetry in favor of negative attitudes versus positive ones. They attributed it to a negativity bias that “weights resemblance to a known negative more heavily than resemblance to a positive” (p. 300). Applied to help seeking scenarios, this would mean that when facing an unknown situation, people would tend to generalize and infer that is more likely that they get a negative rather than a positive outcome from it, so, along with what it was said before, people will be more inclined to think that they will get a “no” when requesting help. Denrell and Le Mens (2011) present a different perspective when trying to explain judgment biases in general. They deviate from the classical inappropriate information processing (depicted among other by Fiske & Taylor, 2007, and Tversky & Kahneman, 1974) and explain this in terms of ‘adaptive sampling’. Adaptive sampling is a sampling mechanism in which the selection of sample items is conditioned by the values of the variable of interest previously observed (Thompson, 2011). Sampling adaptively allows individuals to safeguard themselves from experiences they went through once and turned out to lay negative outcomes. However, it also prevents them from giving a second chance to those experiences to get an updated outcome that could maybe turn into a positive one, a more positive one, or just one that regresses to the mean, whatever direction that implies. That, as Denrell and Le Mens (2011) explained, makes sense: If you go to a restaurant, and you did not like the food, you do not choose that restaurant again. This is what we think could be happening when asking for help: When we get a “no”, we stop asking. And here, we want to provide a complementary explanation for the underestimation of the probability that others comply with our direct help requests based on adaptive sampling. First, we will develop and explain a model that represents the theory. Later on, we will test it empirically by means of experiments, and will elaborate on the analysis of its results.

High pressure processing of swede (Brassica napus): Impact on quality properties

The effects of combined pressure/temperature treatments (200, 400 and 600 MPa, at 20 and 40 °C) on the physical and nutritional properties of swede roots (Brassica napus var. napobrassica) were assessed. Changes induced by high pressure processing (HPP) on the original properties of swede samples were compared with those produced by thermal treatment (blanching). All studied treatments altered the physical properties of swede, resulting in a loss of hardness and water binding capacity. The strongest alteration of texture was observed after HPP at 400 MPa, while 600 MPa was the treatment that better preserved the texture properties of swede. Blanching caused less total colour changes (ΔE) than HPP. Antioxidant properties of swede were measured as total antioxidant capacity, ascorbic acid and total phenol content. All treatments caused a loss of antioxidant capacity, which was less pronounced after HPP at 600 MPa and 20 °C and blanching. Four glucosinolates were detected in swede roots, glucoraphanin, progoitrin, glucobrassicanapin and glucobrassicin. Glucobrassicanapin and glucobrassicin contents were reduced with all studied treatments. Progoitrin content was not affected by blanching and HPP at 200 MPa. HPP at higher pressure levels (400 and 600 MPa), though, induced an increase of progoitrin levels. The results indicated that blanching and HPP at 600 MPa and 20 °C were the treatments that better preserved the original quality properties of swede.

The normal distribution in some constrained sample spaces

Phenomena with a constrained sample space appear frequently in practice. This is the case e.g. with strictly positive data, or with compositional data, like percentages or proportions. If the natural measure of difference is not the absolute one, simple algebraic properties show that it is more convenient to work with a geometry different from the usual Euclidean geometry in real space, and with a measure different from the usual Lebesgue measure, leading to alternative models which better fit the phenomenon under study. The general approach is presented and illustrated using the normal distribution, both on the positive real line and on the D-part simplex. The original ideas of McAlister in his introduction to the lognormal distribution in 1879, are recovered and updated

Functional connectivity of reward processing in the brain

Controversial results have been reported concerning the neural mechanisms involved in the processing of rewards and punishments. On the one hand, there is evidence suggesting that monetary gains and losses activate a similar fronto-subcortical network. On the other hand, results of recent studies imply that reward and punishment may engage distinct neural mechanisms. Using functional magnetic resonance imaging (fMRI) we investigated both regional and interregional functional connectivity patterns while participants performed a gambling task featuring unexpectedly high monetary gains and losses. Classical univariate statistical analysis showed that monetary gains and losses activated a similar fronto-striatallimbic network, in which main activation peaks were observed bilaterally in the ventral striatum. Functional connectivity analysis showed similar responses for gain and loss conditions in the insular cortex, the amygdala, and the hippocampus that correlated with the activity observed in the seed region ventral striatum, with the connectivity to the amygdala appearing more pronounced after losses. Larger functional connectivity was found to the medial orbitofrontal cortex for negative outcomes. The fact that different functional patterns were obtained with both analyses suggests that the brain activations observed in the classical univariate approach identifi es the involvement of different functional networks in the current task. These results stress the importance of studying functional connectivity in addition to standard fMRI analysis in reward-related studies.

Determinants of science-based cooperation: evidence in a sample of small and micro firms

We study the determining factors of cience-based cooperation in the case of small and micro firms. In this research, we propose an analytical framework based on the resource-based view of the firm and we identify a set of organisational characteristics, which we classify as internal, external and structural factors. Each factor can be linked to at least one reason, from the firm¿s point of view, to cooperate with universities and public research centres. Each reason can, in turn, be used as an indicator of a firm¿s organisational needs or organisational capacities. In order to validate the theoretical model, we estimate a logistic regression that models the propensity to participate in science-based cooperation activities within a sample of 285 small and micro firms located in Barcelona. The results show the key role played by the absorptive capacity of new and small companies.

Exploring the use of mobile communications in a sample of older people: Preliminary results of a case study in Los Angeles

This paper introduces a qualitative case study on mobile communication among the older population (60+ years old) conducted in Great Los Angeles (CA, USA) in autumn 2011. Methodology, fieldwork and preliminary results are discussed.Before, country-level data is presented to better understand the specific characteristics of the studied individuals. The section focus is on demographics and on acceptance and use of information and communication technologies (ICT).Preliminary results show that within the sample under study (20 individuals) there is a high number of mobile phone users (15) while among non-mobile users (5), three of them decide to stop using this technology. A majority of mobile phone adopters describe a very limited use of the device for everyday life communications. Finally,while Internet is really popular within the sample (14 users), just 3 individuals go online through their mobile telephone.

Threading libraries performance when applied to image acquisition and processing in a forensic application

Peer-reviewed

Taking on new challenges in multi-word unit processing for Machine Translation

This paper discusses the qualitativecomparative evaluation performed on theresults of two machine translation systemswith different approaches to the processing ofmulti-word units. It proposes a solution forovercoming the difficulties multi-word unitspresent to machine translation by adopting amethodology that combines the lexicongrammar approach with OpenLogos ontologyand semantico-syntactic rules. The paper alsodiscusses the importance of a qualitativeevaluation metrics to correctly evaluate theperformance of machine translation engineswith regards to multi-word units.

Spatial processing for frequency diversity schemes

A novel technique to obtain optimum blind spatialprocessing for frequency diversity spread spectrum (FDSS) communicationsystems is introduced. The sufficient statistics for alinear combiner, which prove ineffective due to the interferers frequencycharacteristics, are modified to yield improved detectionunder partial jamming in the spectral domain. Robustness to partialtime jamming is achieved by extending the notion of replicasover the frequency axis to a repetition over the time variable. Analysisand simulations are provided, showing the advantages of usingFDSS with spatial diversity to combat the interference when it isconfined to a narrow frequency band or short time interval relativeto the desired signal extent in either domain.

Statistical reference criteria for adaptive signal processing in digital communications

A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.