Estudios acerca del establecimiento de conexiones entre enunciados hablados: ¿qué pueden contribuir a la promoción de la construcción de una representación coherente del discurso por parte de los estudiantes?

The aim of this article is to provide an overview of how the establishment of discourse connections among spoken statements has been studied by approaches to discourse analysis and psycholinguistic studies, in order to highlight what variables appear to be important for understanding how comprehension of spoken discourse can be facilitated. The consideration of discourse analysis approaches allows us to think about the role of the establishment of discourse connections among speech acts in the classroom, the uses of contextualization cues by bilingual students, the identification of social and cultural notions in teachers’ discourse, and the interactional effects of teachers’ interventions. Preliminary psycholinguistic studies contribute to our understanding of the role of establishing causal connections and integrating adjacent statements through the presence of discourse markers in the comprehension of spoken discourse by college students. The results of these approaches and studies provide insight into students’ comprehension of classroom discourse, and hold the potential for implications for instruction.El propósito de este artículo es realizar un recorrido a través de enfoques de análisis del discurso y estudios de psicolingüística que han investigado el establecimiento de conexiones entre enunciados hablados, a fin de destacar las variables que parecen ser centrales para facilitar la comprensión. La consideración de los enfoques del análisis del discurso nos permitirán pensar acerca del rol del establecimiento de conexiones entre actos del lenguaje en el aula, las funciones de las claves de contextualización, la identificación de las nociones sociales y culturales en el discurso de los profesores, los efectos de las intervenciones de los profesores en la interacción con los estudiantes. Los estudios preliminares de psicolingüística contribuirán a nuestra comprensión del rol del establecimiento de conexiones causales e integración de enunciados adyacentes a través de marcadores del discurso por parte de estudiantes universitarios. La consideración de estos enfoques y estudios nos ayudarán a pensar acerca de las contribuciones que sus propuestas y métodos pueden hacer al enriquecimiento de nuestro entendimiento de cómo los estudiantes comprenden el discurso producido durante las clases.Fil: Yomha Cevasco, Jazmin. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Broek, Paul van den. Leiden University; Países Bajo

Workshop for annual review of Building Resilient Agro-sylvopastoral Systems in West Africa through Participatory Action Research (BRAS-PAR) Project and planning “Partnerships for Scaling Climate-Smart Agriculture (P4S) Phase II

Building Resilient Agro-sylvo-pastoral Systems in West Africa through Participatory Action Research (BRAS-PAR) is a CCAFS Flagship 2 funded four year (2015-2018) project coordinated by the World Agroforestry (ICRAF) and implemented in collaboration with partners namely national agricultural research institutions (INERA in Burkina Faso, SARI in Ghana, INRAN in Niger and ISRA in Senegal) and the International Union for Conservation of Nature (IUCN in Burkina Faso). BRAS-PAR sought to develop up-scalable technological and social innovations of climatesmart agriculture integrating tree-crop-livestock systems through improved understanding of farmer's perceptions and demands, by addressing barriers to adoption taking into consideration gender and social differentiation. The specific objectives include 1) testing, evaluating and validating with rural communities and other stakeholders, scalable climate-smart models of integrated tree-crop-livestock systems, the dominant farming systems in the region, that include climate-risk management strategies; 2) simulating options for improving water and tree-crop-livestock systems under different climate and socio-economic scenarios using models (WaNuLCAS, SWAT, etc.) for informed decision making; 3) assessing the conditions of success and failure of technological interventions on adaptation to climate change. The work here focus on research that evaluates climate-smart practices and technologies that are defined through participatory identification by multistakeholders in each site. Beyond these sites, the approach capitalizes lessons learnt from on-going climate resilient projects to encourage partners to add missing components to the climate-smart village model or initiate new activities when deemed appropriate. Started in 2015, BRAS-PAR targeted three main outcomes: (i) National agricultural research institutions institutionalize the principles of PAR through integration of non-traditional partners in technologies development to generate wider context specific information to be fed into programs and policies to create the enabling environment for the scaling of CSA technologies; (ii) National extension services, development projects and farmer’s organizations widely disseminate and ensure better access to information on best fit CSA portfolios to cope with climate change; and (iii) The private sector including NGOs (FNGN, Larwaal, ARCAD, Care international), microcredit institutions, agro-dealers, rural radios are scaling up/out relevant CSA portfolios through new incentive programs. This project has ended in December 2018 and the meeting review edthe main achievements. During the same first phase of CCAFS , the project “Partnerships for Scaling (P4S) Climate-Smart Agriculture (P56)” was implemented mainly in East Africa with a focus on supporting countries and partners to plan and program CSA actions. It developed new innovations (e.g., The Compendium and Climate Risk Profiles), refreshed and adapted others (e.g., Climate Wizard, mobile-based monitoring) and collaborated on tools (e.g., Rural Household Multi-Indicator Survey, CSA MRV Profile) to develop a comprehensive set of evidence and information to serve diverse stakeholder needs for situation analysis, targeting and prioritizing, program support and monitoring and evaluation (aka ‘CSA-Plan’, Girvetz et al. 2018). Merging the actions of BRAS-PAR and P4S I to become P4S II was done with the intention to use tools and evidence/lessons learned from the Climate-Smart Villages and other development activities, with existing and new partners through direct scientific support to decision makers (e.g., governments, civil society, and researchers) and capacity building to help bring CSA to scale. The scientific activities will be combined with dedicated communication activities such as photo essays, tweets, blog posts, etc. from field staff and partners to raise the visibility of the project and help show case of its successes in supporting countries and position of ICRAF, CIAT, and CCAFS as the go to research organization for the science of scaling up CSA. The key activity areas of P4S II will be around: supporting CSA investment and programming, de-risking agriculture, digital delivery and monitoring and, communauty based scaling of CSA. The present meeting was thought to plan the new activities around these areas for 2019 and beyond

Integrating Prosodic and Lexical Cues for Automatic Topic Segmentation

We present a probabilistic model that uses both prosodic and lexical cues for the automatic segmentation of speech into topically coherent units. We propose two methods for combining lexical and prosodic information using hidden Markov models and decision trees. Lexical information is obtained from a speech recognizer, and prosodic features are extracted automatically from speech waveforms. We evaluate our approach on the Broadcast News corpus, using the DARPA-TDT evaluation metrics. Results show that the prosodic model alone is competitive with word-based segmentation methods. Furthermore, we achieve a significant reduction in error by combining the prosodic and word-based knowledge sources.Comment: 27 pages, 8 figure

Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as Statement, Question, Backchannel, Agreement, Disagreement, and Apology. Our model detects and predicts dialogue acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialogue act sequence. The dialogue model is based on treating the discourse structure of a conversation as a hidden Markov model and the individual dialogue acts as observations emanating from the model states. Constraints on the likely sequence of dialogue acts are modeled via a dialogue act n-gram. The statistical dialogue grammar is combined with word n-grams, decision trees, and neural networks modeling the idiosyncratic lexical and prosodic manifestations of each dialogue act. We develop a probabilistic integration of speech recognition with dialogue modeling, to improve both speech recognition and dialogue act classification accuracy. Models are trained and evaluated using a large hand-labeled database of 1,155 conversations from the Switchboard corpus of spontaneous human-to-human telephone speech. We achieved good dialogue act labeling accuracy (65% based on errorful, automatically recognized words and prosody, and 71% based on word transcripts, compared to a chance baseline accuracy of 35% and human accuracy of 84%) and a small reduction in word recognition error.Comment: 35 pages, 5 figures. Changes in copy editing (note title spelling changed