Spoken Stories, Spoken Word: An Insurgent Practice for Restorative Education

This paper uses the terminology of whiteness, settler colonialism, culturally responsive pedagogy, and restorative education to interrogate the usage of spoken word in schools. I argue that spoken word can function as a form of resistance to white colonialist practices and as an advocate of emotional learning and critical education. This paper focuses on representation, student empowerment, and identity exploration in the context of education institutions. It crosses borders between education and authenticity, between classrooms and real life, and between teachers and students. I aim to ground this essay in the American Studies discipline as it discusses systems of power in the United States and seeks to disrupt dominant narratives through spoken word as an alternative education strategy for dismantling white supremacy and validating marginalized identities. This work is only a small part of the larger conversation on restorative justice in education

Speech and hand transcribed retrieval

This paper describes the issues and preliminary work involved in the creation of an information retrieval system that will manage the retrieval from collections composed of both speech recognised and ordinary text documents. In previous work, it has been shown that because of recognition errors, ordinary documents are generally retrieved in preference to recognised ones. Means of correcting or eliminating the observed bias is the subject of this paper. Initial ideas and some preliminary results are presented

PRESENCE: A human-inspired architecture for speech-based human-machine interaction

Recent years have seen steady improvements in the quality and performance of speech-based human-machine interaction driven by a significant convergence in the methods and techniques employed. However, the quantity of training data required to improve state-of-the-art systems seems to be growing exponentially and performance appears to be asymptotic to a level that may be inadequate for many real-world applications. This suggests that there may be a fundamental flaw in the underlying architecture of contemporary systems, as well as a failure to capitalize on the combinatorial properties of human spoken language. This paper addresses these issues and presents a novel architecture for speech-based human-machine interaction inspired by recent findings in the neurobiology of living systems. Called PRESENCE-"PREdictive SENsorimotor Control and Emulation" - this new architecture blurs the distinction between the core components of a traditional spoken language dialogue system and instead focuses on a recursive hierarchical feedback control structure. Cooperative and communicative behavior emerges as a by-product of an architecture that is founded on a model of interaction in which the system has in mind the needs and intentions of a user and a user has in mind the needs and intentions of the system

Search of spoken documents retrieves well recognized transcripts

This paper presents a series of analyses and experiments on spoken document retrieval systems: search engines that retrieve transcripts produced by speech recognizers. Results show that transcripts that match queries well tend to be recognized more accurately than transcripts that match a query less well. This result was described in past literature, however, no study or explanation of the effect has been provided until now. This paper provides such an analysis showing a relationship between word error rate and query length. The paper expands on past research by increasing the number of recognitions systems that are tested as well as showing the effect in an operational speech retrieval system. Potential future lines of enquiry are also described

Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions

Comprehension of spoken natural language is an essential component for robots to communicate with human effectively. However, handling unconstrained spoken instructions is challenging due to (1) complex structures including a wide variety of expressions used in spoken language and (2) inherent ambiguity in interpretation of human instructions. In this paper, we propose the first comprehensive system that can handle unconstrained spoken language and is able to effectively resolve ambiguity in spoken instructions. Specifically, we integrate deep-learning-based object detection together with natural language processing technologies to handle unconstrained spoken instructions, and propose a method for robots to resolve instruction ambiguity through dialogue. Through our experiments on both a simulated environment as well as a physical industrial robot arm, we demonstrate the ability of our system to understand natural instructions from human operators effectively, and how higher success rates of the object picking task can be achieved through an interactive clarification process.Comment: 9 pages. International Conference on Robotics and Automation (ICRA) 2018. Accompanying videos are available at the following links: https://youtu.be/_Uyv1XIUqhk (the system submitted to ICRA-2018) and http://youtu.be/DGJazkyw0Ws (with improvements after ICRA-2018 submission

Second-generation adolescents’ competencies and the role of integration policies

Immigration into the OECD countries has seen a sharp increase since the middle of the 1980s, even if not at a constant rate. Integration policies are a fundamental tool to help the newly arrived to integrate and assimilate with the native population. While the literature on the immigrants’ integration level is very rich for settlement countries (USA, Canada, Australia and New Zealand) and for the few European countries that have a long tradition of immigration (Germany, UK, France), very little is yet known about other European economies that have only recently become destination countries. Indeed, the availability of data has made difficult to carry out comparative analysis of the integration process of immigrants in most of the EU countries, particularly for the second-generation. This research wants to fill this gap, analysing the role of the socio-economic background in the educational outcome of immigrants. Furthermore, we demonstrate how the effect of the socio-economic background is more or less pronounced in different EU countries that adopt different integration policies and have different education systems. In this work, we concentrate on second-generation adolescents and compare their performances with that of native adolescents and with that of first generation adolescents. The chosen indicator is the score obtained in the 2012 PISA test by each student (native, first and second-generation immigrant) in reading. We compare the results obtained for each of the EU15 member states and for the settlement countries. The results, in line with the prevalent literature, show a strong impact of the socio-economic background on the immigrant adolescents’ performances. The effect is weaker in those countries where the integration policies concern disadvantaged children since an early age