Humanising Text-to-Speech Through Emotional Expression in Online Courses

This paper outlines an innovative approach to evaluate the emotional content of three online courses using the affective computing approach of prosody detection on two different text-to-speech (TTS) voices in conjunction with human raters judging the emotional content of the text. This work intends to establish the potential variation on the emotional delivery of online educational resources through the use of synthetic voice, which automatically articulates text into audio. Preliminary results from this pilot research suggest that about one out of every three sentences (35%) in a MOOC contained emotional text and two existing assistive technology voices had poor emotional alignment when reading this text. Synthetic voices were more likely to be overly negative when considering their expression as compared to the emotional content of the text they are reading, which was most frequently neutral. We also analyzed a synthetic voice for which we configured the emotional expression to align with course text, which showed promising improvements

Construction of ETSEIB's website Chatbot with IBM Watson Assistant

Aquest projecte tracta sobre la creació d’un assistent virtual (xatbot) per la web de l‟Escola Tècnica Superior d‟Enginyeria Industrial de Barcelona (ETSEIB) amb el programa Watson Assistant. Els principals objectius d'aquest treball són disminuir la càrrega de treball de les persones encarregades de respondre les preguntes dels usuaris i millorar l'experiència de la pàgina web. En aquest treball consta un apartat teòric, on s'explica la definició i l'estat de l'art dels chatbots, així com diferents suports per crear-los. A continuació, s'explica més a fons el funcionament de IBM Watson Assistant, que és l'eina utilitzada per crear el xatbot. Després de presentar l'eina, s'explica la metodologia emprada en la ideació i la construcció d'aquest. Durant el capítol de la metodologia es fa un paral·lelisme entre com es desenvoluparia el producte per un equip d'IBM i com ho he desenvolupat jo com a particular. Finalment s'exposa el xatbot a experimentació i se n'extreuen conclusions. Es pot concloure que és una bona manera de donar resposta a preguntes freqüents que entrin dins de l'abast, disminuiria el treball mecànic de resolució de dubtes que hi ha actualment de forma manual i ajuda en la navegació de la pàgina webEste proyecto trata sobre la creación de un asistente virtual (chatbot) para la web de la Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB) con el programa Watson Assistant. Los objetivos principales de este trabajo son disminuir la carga de trabajo de las personas encargadas de responder las preguntas de los usuarios y mejorar la experiencia de la página web. En este trabajo consta un apartado teórico, donde se explica la definición y el estado del arte de los chatbots, así como diferentes soportes para la creación de estos. A continuación, se explica más a fondo el funcionamiento de IBM Watson Assistant, que es la herramienta utilizada para crear el chatbot. Después de presentar la herramienta, se explica la metodología emprada en la ideación y construcción de este. Durante el capítulo de la metodología se hace un paralelismo entre cómo se desarrollaría el producto por un equipo de IBM y como lo he desarrollado yo como particular. Finalmente se expone el chatbot a experimentación y se extraen conclusiones. Se puede concluir que es una buena manera de dar respuesta a preguntas frecuentes que entren dentro del alcance, disminuiría el trabajo mecánico de resolución de dudas que existe actualmente de forma manual y ayuda en la navegación de la página webThis project deals with the creation of a virtual assistant (chatbot) for Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB) website with the Watson Assistant program. The main objectives of this work are to reduce the workload of the people in charge of answering user questions and to improve the experience of the website. In this work there is a theoretical section, where the definition and the state of the art of chatbots are explained, as well as different supports for their creation. Next, the operation of IBM Watson Assistant, which is the tool used to create the chatbot, is explained in more depth. After presenting the tool, the methodology used in its ideation and construction is explained. During the methodology chapter, a parallelism is made between how would the product be developed by an IBM team and how I have developed it as an individual. Finally, the chatbot is exposed to experimentation and conclusions are drawn. It can be concluded that it is a good way to answer frequently asked questions that fall within the scope of the chatbot, it would reduce the mechanical and repetitive work of resolving questions manually and it would help to navigate the web pag

On the Development of Adaptive and User-Centred Interactive Multimodal Interfaces

Multimodal systems have attained increased attention in recent years, which has made possible important improvements in the technologies for recognition, processing, and generation of multimodal information. However, there are still many issues related to multimodality which are not clear, for example, the principles that make it possible to resemble human-human multimodal communication. This chapter focuses on some of the most important challenges that researchers have recently envisioned for future multimodal interfaces. It also describes current efforts to develop intelligent, adaptive, proactive, portable and affective multimodal interfaces

Blending big data analytics : review on challenges and a recent study

With the collection of massive amounts of data every day, big data analytics has emerged as an important trend for many organizations. These collected data can contain important information that may be key to solving wide-ranging problems, such as cyber security, marketing, healthcare, and fraud. To analyze their large volumes of data for business analyses and decisions, large companies, such as Facebook and Google, adopt analytics. Such analyses and decisions impact existing and future technology. In this paper, we explore how big data analytics is utilized as a technique for solving problems of complex and unstructured data using such technologies as Hadoop, Spark, and MapReduce. We also discuss the data challenges introduced by big data according to the literature, including its six V's. Moreover, we investigate case studies of big data analytics on various techniques of such analytics, namely, text, voice, video, and network analytics. We conclude that big data analytics can bring positive changes in many fields, such as education, military, healthcare, politics, business, agriculture, banking, and marketing, in the future. © 2013 IEEE

Conversational Agents in Education – A Systematic Literature Review

Conversational Agents (CAs) are widely spread in a variety of domains, such as health and customer service. There is a recent trend of increasing publications and implementations of CAs in education. We conduct a systematic literature review to identify common methodologies, pedagogical CA roles, addressed target groups, the technologies and theories behind, as well as human-like design aspects. The initially found 3329 records were systematically reduced to 252 fully coded articles. Based on the analysis of the codings, we derive further research streams. Our results reveal a research gap for long-term studies on the use of CAs in education, and there is insufficient holistic design knowledge for pedagogical CAs. Moreover, target groups other than academic students are rarely considered. We condense our findings in a morphological box and conclude that pedagogical CAs have not yet reached their full potential of long-term practical application in education

Answering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs

Direct answering of questions that involve multiple entities and relations is a challenge for text-based QA. This problem is most pronounced when answers can be found only by joining evidence from multiple documents. Curated knowledge graphs (KGs) may yield good answers, but are limited by their inherent incompleteness and potential staleness. This paper presents QUEST, a method that can answer complex questions directly from textual sources on-the-fly, by computing similarity joins over partial results from different documents. Our method is completely unsupervised, avoiding training-data bottlenecks and being able to cope with rapidly evolving ad hoc topics and formulation style in user questions. QUEST builds a noisy quasi KG with node and edge weights, consisting of dynamically retrieved entity names and relational phrases. It augments this graph with types and semantic alignments, and computes the best answers by an algorithm for Group Steiner Trees. We evaluate QUEST on benchmarks of complex questions, and show that it substantially outperforms state-of-the-art baselines

Special Issue on the AMCIS 2001 Workshops: A Three Level Approach to Managing Curricular Technology Integration Strategically at Bentley College

This paper presents an overview of the unprecedented array of technologies that are employed at Bentley College. These technologies are used in traditional, on-campus courses, and in videoconference and web-based distance learning courses. The paper discusses how Bentley approaches the integration of technology into the curriculum, guided by a three-level approach