Speech Emotion Recognition Considering Local Dynamic Features

Recently, increasing attention has been directed to the study of the speech emotion recognition, in which global acoustic features of an utterance are mostly used to eliminate the content differences. However, the expression of speech emotion is a dynamic process, which is reflected through dynamic durations, energies, and some other prosodic information when one speaks. In this paper, a novel local dynamic pitch probability distribution feature, which is obtained by drawing the histogram, is proposed to improve the accuracy of speech emotion recognition. Compared with most of the previous works using global features, the proposed method takes advantage of the local dynamic information conveyed by the emotional speech. Several experiments on Berlin Database of Emotional Speech are conducted to verify the effectiveness of the proposed method. The experimental results demonstrate that the local dynamic information obtained with the proposed method is more effective for speech emotion recognition than the traditional global features.Comment: 10 pages, 3 figures, accepted by ISSP 201

Tracking the Expression of Annoyance in Call Centers

Machine learning researchers have dealt with the identification of emo- tional cues from speech since it is research domain showing a large number of po- tential applications. Many acoustic parameters have been analyzed when searching for cues to identify emotional categories. Then classical classifiers and also out- standing computational approaches have been developed. Experiments have been carried out mainly over induced emotions, even if recently research is shifting to work over spontaneous emotions. In such a framework, it is worth mentioning that the expression of spontaneous emotions depends on cultural factors, on the particu- lar individual and also on the specific situation. In this work, we were interested in the emotional shifts during conversation. In particular we were aimed to track the annoyance shifts appearing in phone conversations to complaint services. To this end we analyzed a set of audio files showing different ways to express annoyance. The call center operators found disappointment, impotence or anger as expression of annoyance. However, our experiments showed that variations of parameters derived from intensity combined with some spectral information and suprasegmental fea- tures are very robust for each speaker and annoyance rate. The work also discussed the annotation problem arising when dealing with human labelling of subjective events. In this work we proposed an extended rating scale in order to include anno- tators disagreements. Our frame classification results validated the chosen annota- tion procedure. Experimental results also showed that shifts in customer annoyance rates could be potentially tracked during phone callsSpanish Mineco under grant TIN2014- 54288-C4-4-R H2020 EU under Empathic RIA action number 769872

Rank-based poverty measures and poverty ordering with an application to Tunisia

Using the normative approach, we develop a class of poverty measures that is function of a weighting system. Each particular weighting function corresponds to a particular social judgment. This offers the decision-maker a large selection of social preferences functions, and he can choose the one that best represents his social judgment. We also develop new concepts of a-extended TIP curves. They are used to establish the conditions of the robust and unanimous poverty ranking of our measures. These conditions are in terms of second-and higher-degree TIP dominance. Finally, we provide an empirical illustration using Tunisian data on the 2005–2010 period.info:eu-repo/semantics/publishedVersio

Placentation defects are highly prevalent in embryonic lethal mouse mutants.

Large-scale phenotyping efforts have demonstrated that approximately 25-30% of mouse gene knockouts cause intrauterine lethality. Analysis of these mutants has largely focused on the embryo and not the placenta, despite the crucial role of this extraembryonic organ for developmental progression. Here we screened 103 embryonic lethal and sub-viable mouse knockout lines from the Deciphering the Mechanisms of Developmental Disorders program for placental phenotypes. We found that 68% of knockout lines that are lethal at or after mid-gestation exhibited placental dysmorphologies. Early lethality (embryonic days 9.5-14.5) is almost always associated with severe placental malformations. Placental defects correlate strongly with abnormal brain, heart and vascular development. Analysis of mutant trophoblast stem cells and conditional knockouts suggests that a considerable number of factors that cause embryonic lethality when ablated have primary gene function in trophoblast cells. Our data highlight the hugely under-appreciated importance of placental defects in contributing to abnormal embryo development and suggest key molecular nodes that govern placenta formation

Human and mouse essentiality screens as a resource for disease gene discovery.

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery

Systematic screening for skin, hair, and nail abnormalities in a large-scale knockout mouse program

The International Knockout Mouse Consortium was formed in 2007 to inactivate (“knockout”) all protein-coding genes in the mouse genome in embryonic stem cells. Production and characterization of these mice, now underway, has generated and phenotyped 3,100 strains with knockout alleles. Skin and adnexa diseases are best defined at the gross clinical level and by histopathology. Representative retired breeders had skin collected from the back, abdomen, eyelids, muzzle, ears, tail, and lower limbs including the nails. To date, 169 novel mutant lines were reviewed and of these, only one was found to have a relatively minor sebaceous gland abnormality associated with follicular dystrophy. The B6N(Cg)-Far2tm2b(KOMP)Wtsi/2J strain, had lesions affecting sebaceous glands with what appeared to be a secondary follicular dystrophy. A second line, B6N(Cg)-Ppp1r9btm1.1(KOMP)Vlcg/J, had follicular dystrophy limited to many but not all mystacial vibrissae in heterozygous but not homozygous mutant mice, suggesting that this was a nonspecific background lesion. We discuss potential reasons for the low frequency of skin and adnexal phenotypes in mice from this project in comparison to those seen in human Mendelian diseases, and suggest alternative approaches to identification of human disease-relevant models.This work was supported by grants from the National Institutes of Health (R21-AR063781 and U42-OD011185). Shared services at The Jackson Laboratory are subsidized by a National Cancer Institute Core Grant (P30-CA034196). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript