El surgimiento de la radiodifusión pública en Hispanoamérica. Contexto, modelos y el estudio de un caso singular : el SODRE, la radio pública estatal de Uruguay (1929)

Este artículo describe y analiza las características específicas de una de las primeras radios públicas de Hispanoamérica, la emisora CX6 SODRE de Uruguay creada en 1929, que aún continúa al aire. La peculiaridad mayor del SODRE radica en un diseño institucional de doble vía, que supuso la instalación al mismo tiempo de la radio y la Discoteca Nacional, de un conjunto de conjuntos estables de música que debían realizar sus conciertos en una sala comprada a tales efectos, que a su vez eran transmitidos por la emisora. De este modo, mientras que en general se ve el momento de la aparición de la radio como el del desplazamiento a un segundo plano de modelo de los conciertos públicos característicos del siglo XIX, el SODRE mantuvo las dos formas de comunicación vivas y retroalimentándose recíprocamente en un peculiar modelo de oferta cultural que alternaba las prácticas culturales de lo “aurático” con las de lo “tecnológico” (Benjamin 1968).This article describes and analyzes the specific characteristics of one of the first public radio stations of Spanish America, CX6 SODRE of Uruguay created in 1929, which still continues to air. The major peculiarity of the SODRE derives from an institutional design of double route, which implies on the one hand, the installation of the public broadcasting station with its correspondant National Discotheque, and on the other hand, the creation of a set of stable music groups which offered concerts for the public radio and for the general public in a theatre bought to such effects by the State. Thus, whereas in general the appearance of the radio is seen as the displacement of 19th century typical cultural practices such as live concerts to a second scenario, the SODRE kept both forms of communication alive in a peculiar model of cultural offer which alternated the “auratical” with the “techonological” (Benjamin 1968)

A Differentiable Generative Adversarial Network for Open Domain Dialogue

Paper presented at the IWSDS 2019: International Workshop on Spoken Dialogue Systems Technology, Siracusa, Italy, April 24-26, 2019This work presents a novel methodology to train open domain neural dialogue systems within the framework of Generative Adversarial Networks with gradient-based optimization methods. We avoid the non-differentiability related to text-generating networks approximating the word vector corresponding to each generated token via a top-k softmax. We show that a weighted average of the word vectors of the most probable tokens computed from the probabilities resulting of the top-k softmax leads to a good approximation of the word vector of the generated token. Finally we demonstrate through a human evaluation process that training a neural dialogue system via adversarial learning with this method successfully discourages it from producing generic responses. Instead it tends to produce more informative and variate ones.This work has been partially funded by the Basque Government under grant PRE_2017_1_0357, by the University of the Basque Country UPV/EHU under grant PIF17/310, and by the H2020 RIA EMPATHIC (Grant N: 769872)

A multilingual neural coaching model with enhanced long-term dialogue structure

In this work we develop a fully data-driven conversational agent capable of carrying out motivational coach- ing sessions in Spanish, French, Norwegian, and English. Unlike the majority of coaching, and in general well-being related conversational agents that can be found in the literature, ours is not designed by hand- crafted rules. Instead, we directly model the coaching strategy of professionals with end users. To this end, we gather a set of virtual coaching sessions through a Wizard of Oz platform, and apply state of the art Natural Language Processing techniques. We employ a transfer learning approach, pretraining GPT2 neural language models and fine-tuning them on our corpus. However, since these only take as input a local dialogue history, a simple fine-tuning procedure is not capable of modeling the long-term dialogue strategies that appear in coaching sessions. To alleviate this issue, we first propose to learn dialogue phase and scenario embeddings in the fine-tuning stage. These indicate to the model at which part of the dialogue it is and which kind of coaching session it is carrying out. Second, we develop a global deep learning system which controls the long-term structure of the dialogue. We also show that this global module can be used to visualize and interpret the decisions taken by the the conversational agent, and that the learnt representations are comparable to dialogue acts. Automatic and human evaluation show that our proposals serve to improve the baseline models. Finally, interaction experiments with coaching experts indicate that the system is usable and gives rise to positive emotions in Spanish, French and English, while the results in Norwegian point out that there is still work to be done in fully data driven approaches with very low resource languages.This work has been partially funded by the Basque Government under grant PRE_2017_1_0357 and by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 769872

Perceptual borderline for balancing multi-class spontaneous emotional data

Speech is a behavioural biometric signal that can provide important information to understand the human intends as well as their emotional status. The paper is centered on the speech-based identification of the seniors’s emotional status during their interaction with a virtual agent playing the role of a health professional coach. Under real conditions, we can just identify a small set of task-dependent spontaneous emotions. The number of identified samples is largely different for each emotion, which results in an imbalanced dataset problem. This research proposes the dimensional model of emotions as a perceptual representation space alternative to the generally used acoustic one. The main contribution of the paper is the definition of a perceptual borderline for the oversampling of minority emotion classes in this space. This limit, based on arousal and valence criteria, leads to two methods of balancing the data: the Perceptual Borderline oversampling and the Perceptual Borderline SMOTE (Synthetic Minority Oversampling Technique). Both methods are implemented and compared to state-of-the-art approaches of Random oversampling and SMOTE. The experimental evaluation was carried out on three imbalanced datasets of spontaneous emotions acquired in human-machine scenarios in three different cultures: Spain, France and Norway. The emotion recognition results obtained by neural networks classifiers show that the proposed perceptual oversampling methods led to significant improvements when compared with the state-of-the art, for all scenarios and languages.The research presented in this paper is conducted as partof the project EMPATHIC and of the MENHIR MSCAaction that have received funding from the European Union’s Horizon 2020 research and innovation program under grant agreements No 769872 an No 823907 respective

Autoestima en docentes de instituciones de jornada escolar completa en Pomabamba, Ancash

El presente estudio tuvo como objetivo determinar el nivel de autoestima en los docentes de secundaria de instituciones educativas públicas de Jornada Escolar Completa del distrito de Pomabamba, en Áncash. Se llevó a cabo una investigación de enfoque cuantitativo, con un diseño no experimental, transversal, descriptivo simple. Se contó con una muestra no probabilística, por conveniencia, de 45 docentes, de los cuales 20 eran mujeres y 25 eran varones. El instrumento utilizado para recoger datos fue el test de Autoestima en Profesores de Arzola y Collarte. Los resultados mostraron que el 95.5% de los participantes se ubicaron en un nivel alto de autoestima general, así como en las dimensiones de Yo soy y Yo siento, mientras que en la dimensión Yo hago el porcentaje fue de 93,3 %. En conclusión, los docentes manifiestan un nivel alto de autoestima.The objective of the present study was to determine the level of self-esteem in secondary school teachers of public educational institutions of Full School Day of the district of Pomabamba, in Ancash. A quantitative approach research was carried out, with a nonexperimental, cross-sectional, simple descriptive design. A non-probabilistic sample was used, for convenience, of 45 teachers, of whom 20 were women and 25 were men. The instrument used to collect data was the Arzola and Collarte Teacher Self-Esteem test. The results showed that 95.5% of the participants were located in a high level of general selfesteem, as well as in the dimensions of I am and I feel, while in the I do dimension the percentage was 93.3%. In conclusion, teachers show a high level of self-esteem

O surgimento da radiodifusão pública na América Hispânica. Contexto, modelos e o estudo de um caso singular: Sodre, a rádio pública estatal do Uruguai (1929)

Este artigo descreve e analisa as características específicas de uma das primeiras rádios públicas da América hispânica, a emissora CX6 Sodre de Uruguai, que foi criada em 1929 e continua ao ar. A peculiaridade maior do Serviço Oficial de Difusão Radioelétrica (Sodre) do Uruguai se baseia num desenho institucional de dupla via, que supôs a instalação, junto à rádio e à Discoteca Nacional, de um conjunto de corpos estáveis de música que deviam realizar concertos numa sala comprada pelo Estado com essa finalidade, a partir da qual, por sua vez, as apresentações eram transmitidos pela emissora. Deste modo, enquanto se vê o momento de criação da rádio como o deslocamento a um segundo plano do modelo de concertos públicos característicos do século XIX, o Sodre manteve as duas formas de comunicação vivas, retroalimentando-se num peculiar modelo de oferta cultural que alternava as práticas culturais do “aurático” com as do “tecnológico” (Benjamin, 1968)

Audio Embeddings help to learn better dialogue policies

Presentado en ASRU 2021, Cartagena (Colombia), 13-17 diciembre 2021Neural transformer architectures have gained a lot of interest for text-based dialogue management in the last few years. They have shown high learning capabilities for open domain dialogue with huge amounts of data and also for domain adaptation in task-oriented setups. But the potential benefits of exploiting the users’ audio signal have rarely been ex- plored in such frameworks. In this work, we combine text dialogue history representations generated by a GPT-2 model with audio embeddings obtained by the recently released Wav2Vec2 transformer model. We jointly fine-tune these models to learn dialogue policies via supervised learning and two policy gradient-based reinforcement learning algorithms. Our experimental results, using the DSTC2 dataset and a sim- ulated user model capable of sampling audio turns, reveal that audio embeddings lead to overall higher task success (than without using audio embeddings) with statistically significant results across evaluation metrics and training algorithms

Energetic study of cardioplegic hearts under ischaemia/reperfusion and [Ca2+] changes in cardiomyocytes of guinea-pig: Mitochondrial role

Abstract Aim: To study the role of mitochondria in the recovery of guinea-pig hearts exposed to high-K+-cardioplegia (CPG) and ischaemia/reperfusion (I/R) Methods: We measured contractility and heat release in perfused guineapig hearts and cytosolic and mitochondrial Ca2+ by epifluorescence and confocal microscopy in isolated cardiomyocytes loaded with Fluo-4 or Rhod-2. Results: In hearts, CPG increased the postischaemic contractile recovery, and this was potentiated by the mNCX blocker clonazepam and the mKATP opener diazoxide, which also prevented the fall in muscle economy. Moreover, CPG prevented the stunning induced by ouabain, which was reduced by clonazepam. In cardiomyocytes, CPG increased fluorescent signals of cytosolic and mitochondrial Ca2+, while the addition of a mNCX blocker (CGP37157) increased cytosolic but reduced mitochondrial [Ca2+]. Ouabain in CPG increased cytosolic Ca2+ and resting heat, but the addition of CGP37157 reduced them, as well as mitochondrial Ca2+. Conclusions: CPG, diazoxide and clonazepam improve postischaemic recovery, respectively, by increasing the Ca2+ cycling and by reducing the mitochondrial Ca2+ uptake either by uniporter or by mNCX. The mitochondria compete with the leaky sarcoplasmic reticulum (SR) as sink of Ca2+ in guinea-pig hearts, affecting the postischaemic contractility. CPG also prevented the ouabain-induced dysfunction by avoiding the Ca2+ overload. Ouabain reduced the synergism between CPG and clonazepam suggesting that [Na+]i and SR load influence the mNCX role.Fil: Ragone, María Inés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas. Cátedra de Farmacología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Torres, N. S.. Cardiovascular Research And Training Institute; Estados UnidosFil: Consolini, A. E.. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas. Cátedra de Farmacología; Argentin

User-Aware Dialogue Management Policies over Attributed Bi-Automata

Designing dialogue policies that take user behavior into account is complicated due to user vari- ability and behavioral uncertainty. Attributed Prob- abilistic Finite State Bi-Automata (A-PFSBA) have proven to be a promising framework to develop dia- logue managers that capture the users’ actions in its structure and adapt to them online, yet developing poli- cies robust to high user uncertainty is still challenging. In this paper, the theoretical A-PFSBA dialogue man- agement framework is augmented by formally defining the notation of exploitation policies over its structure. Under such definition, multiple path based policies are implemented, those that take into account external in- formation and those which do not. These policies are evaluated on the Let’s Go corpus, before and after an online learning process whose goal is to update the ini- tial model through the interaction with end-users. In these experiments the impact of user uncertainty and the model structural learning is thoroughly analyzedSpanish Minister of Science under grants TIN2014-54288-C4- 4-R and TIN2017-85854-C4-3-R European Commission H2020 SC1-PM15 EMPATHIC project, RIA grant 69872