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

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

Developmental synaptic changes at the transient olivocochlear-inner hair cell synapse

In the mature mammalian cochlea, inner hair cells (IHCs) are mainly innervated by afferent fibers that convey sound information to the CNS. During postnatal development, however, medial olivocochlear (MOC) efferent fibers transiently innervate the IHCs. The MOC-IHC synapse, functional from postnatal day 0 (P0) to hearing onset (P12), undergoes dramatic changes in the sensitivity to acetylcholine (ACh) and in the expression of key postsynaptic proteins. To evaluate whether there are associated changes in the properties of ACh release during this period, we used a cochlear preparation from mice of either sex at P4, P6-P7, and P9-P11 and monitored transmitter release from MOC terminals in voltage-clamped IHCs in the whole-cell configuration. The quantum content increased 5.6× from P4 to P9-P11 due to increases in the size and replenishment rate of the readily releasable pool of synaptic vesicles without changes in their probability of release or quantum size. This strengthening in transmission was accompanied by changes in short-term plasticity properties, which switched from facilitation at P4 to depression at P9-P11. We have previously shown that at P9-P11, ACh release is supported by P/Q- and N-type voltage-gated calcium channels (VGCCs) and negatively regulated by BK potassium channels activated by Ca2+ influx through L-type VGCCs. We now show that at P4 and P6-P7, release is mediated by P/Q-, R- and L-type VGCCs. Interestingly, L-type VGCCs have a dual role: they both support release and fuel BK channels, suggesting that at immature stages presynaptic proteins involved in release are less compartmentalized.Fil: Kearney, Graciela Inés. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Zorrilla de San Martín, Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Vattino, Lucas Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Elgoyhen, Ana Belen. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Farmacologia; ArgentinaFil: Wedemeyer, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Katz, Eleonora. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Fisiología, Biología Molecular y Celular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentin

Study of Kinematics in Secondary School: Experience with the Tool Modellus

Las dificultades de los estudiantes en el aprendizaje cuando comprenden modelos, analizan fenómenos y resuelven problemas en Física nos llevó a proponer la utilización del programa Modellus para favorecer el aprendizaje de temas de Cinemática. Desarrollamos la experiencia en una escuela secundaria estatal de San Juan (Argentina) con estudiantes de sexto año (edad promedio: 18 años). Los resultados obtenidos permitirían inferir una respuesta favorable de los estudiantes para usar recursos TIC y una incidencia positiva de las simulaciones mediante la aplicación matemática que permite el modelo científico. Esto hace posible recomendar el software Modellus para aprender Cinemática.The students' learning difficulties, when they approach models, analyze phenomena and solve problems in Physics, led us to propose the use of Modellus programme to favour the learning of kinematics topics. We develop an experience in a state secondary school in San Juan (Argentina) with students attending the last course (average age: 18 years old). The results suggest a favorable response from students to use ICT resources and a positive impact in applying mathematical simulations that the scientific model allows. Consequently, it appears that the software Modellus could be recommended in order to learn Kinematics

Corrective Focus Detection in Italian Speech Using Neural Networks

The corrective focus is a particular kind of prosodic prominence where the speaker is intended to correct or to emphasize a concept. This work develops an Artificial Cognitive System (ACS) based on Recurrent Neural Networks that analyzes suitablefeatures of the audio channel in order to automatically identify the Corrective Focus on speech signals. Two different approaches to build the ACS have been developed. The first one addresses the detection of focused syllables within a given Intonational Unit whereas the second one identifies a whole IU as focused or not. The experimental evaluation over an Italian Corpus has shown the ability of the Artificial Cognitive System to identify the focus in the speaker IUs. This ability can lead to further important improvements in human-machine communication. The addressed problem is a good example of synergies between Humans and Artificial Cognitive Systems.The research leading to the results in this paper has been conducted in the project EMPATHIC (Grant N: 769872) that received funding from the European Union’s Horizon2020 research and innovation programme.Additionally, this work has been partially funded by the Spanish Minister of Science under grants TIN2014-54288-C4-4-R and TIN2017-85854-C4-3-R, by the Basque Government under grant PRE_2017_1_0357,andby the University of the Basque Country UPV/EHU under grantPIF17/310

Are we moving towards a sustainable viticulture? An exploratory study of the argentine wine industry

Esta investigación pretende contribuir al debate sobre la sostenibilidad de la industriadel vino de Argentina. Para ello, se identificaron áreas del Protocolo de Autoevaluaciónde Sustentabilidad Vitivinícola de Bodegas de Argentina donde será necesarioactuar si se desea avanzar hacia una vitivinicultura más sostenible. El tamaño de losestablecimientos vitivinícolas parece ser un factor clave en la gestión de la sostenibilidad.Los establecimientos más grandes, en comparación con los más pequeños,implementan prácticas de manejo significativamente más sostenibles. Los resultadosde la investigación pueden ser de especial utilidad para los responsables de la formulaciónde políticas, viticultores, propietarios de bodegas y demás actores del sectorinteresados en hacer que la viticultura y la elaboración de vinos sean más sostenibles.This study contributes to the debate on sustainability in the wine industry of Argentina. In order to do this, we identified areas of the Protocolo de Autoevaluación de Sustentabilidad Vitivinícola de Bodegas de Argentina which will require further work in case one wants to move towards a more sustainable viticulture. Size of wineries and vineyards appears to be an important factor in managing sustainability. Larger viticultural establishments, compared to smaller ones, implement significantly more sustainable management practices. These results may be of particular use for policy makers, winegrowers, winery owners, and other stakeholders interested in making winegrowing and winemaking more sustainable.Fil: Salas Zorrilla, Javiera. Universidad Nacional de Cuyo. Facultad de Ciencias Económicas; ArgentinaFil: Farreras González, Verónica Inés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Económicas; Argentin

Dialogue Management and Language Generation for a Robust Conversational Virtual Coach: Validation and User Study

Designing human–machine interactive systems requires cooperation between different disciplines is required. In this work, we present a Dialogue Manager and a Language Generator that are the core modules of a Voice-based Spoken Dialogue System (SDS) capable of carrying out challenging, long and complex coaching conversations. We also develop an efficient integration procedure of the whole system that will act as an intelligent and robust Virtual Coach. The coaching task significantly differs from the classical applications of SDSs, resulting in a much higher degree of complexity and difficulty. The Virtual Coach has been successfully tested and validated in a user study with independent elderly, in three different countries with three different languages and cultures: Spain, France and Norway.The research presented in this paper has been conducted as part of the project EMPATHIC that has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant No. 769872. Additionally, this work has been partially funded by projects BEWORD and AMIC-PC of the Minister of Science of Technology, under Grant Nos. PID2021-126061OB-C42 and PDC2021-120846-C43, respectively. Vázquez and López Zorrilla received a PhD scholarship from the Basque Government, with Grant Nos. PRE 2020 1 0274 and PRE 2017 1 0357, respectively

Can Spontaneous Emotions be Detected from Speech on TV Political Debates?

Accepted paperDecoding emotional states from multimodal signals is an increasingly active domain, within the framework of affective computing, which aims to a better understanding of Human-Human Communication as well as to improve Human- Computer Interaction. But the automatic recognition of sponta- neous emotions from speech is a very complex task due to the lack of a certainty of the speaker states as well as to the difficulty to identify a variety of emotions in real scenarios. In this work we explore the extent to which emotional states can be decoded from speech signals extracted from TV political debates. The labelling procedure was supported by perception experiments where only a small set of emotions has been identified. In addition, some scaled judgements of valence, arousal and dominance were also provided. In this framework the paper shows meaningful comparisons between both, the dimensional and the categorical models of emotions, which is a new con- tribution when dealing with spontaneous emotions. To this end Support Vector Machines (SVM) as well as Feedforward Neural Networks (FNN) have been proposed to develop classifiers and predictors. The experimental evaluation over a Spanish corpus has shown the ability of both models to be identified in speech segments by the proposed artificial systems.This work has been partially funded by the Spanish Government under grant TIN2017-85854-C4-3-R (AEI/FEDER,UE) and conducted in the project EMPATHIC (Grant n769872) funded by the European Union’s H2020 research andinnovation program

Las prácticas experimentales sobre magnetismo en libros de texto de educación secundaria básica

El objetivo de este trabajo es analizar las prácticas experimentales en libros de texto de educación secundaria básica de Argentina relacionadas con los fenómenos magnéticos y electromagnéticos. Examinamos, desde un abordaje cualitativo, su inserción en cada libro, el tratamiento de los contenidos disciplinares y las características intrínsecas relacionadas con su apertura. Los criterios de análisis construidos se centran en aspectos didácticos y disciplinares. Hemos encontrado diferencias significativas en las prácticas experimentales incluidas en los libros de la muestra que se relacionan con el lugar de inserción en el libro y de abordaje en relación con los contenidos teóricos, y con sus características de apertura, lo cual podría ayudar al docente en el proceso de selección de las prácticas experimentales