Multi-channel Transformers for Multi-articulatory Sign Language Translation

Sign languages use multiple asynchronous information channels (articulators), not just the hands but also the face and body, which computational approaches often ignore. In this paper we tackle the multi-articulatory sign language translation task and propose a novel multi-channel transformer architecture. The proposed architecture allows both the inter and intra contextual relationships between different sign articulators to be modelled within the transformer network itself, while also maintaining channel specific information. We evaluate our approach on the RWTH-PHOENIX-Weather-2014T dataset and report competitive translation performance. Importantly, we overcome the reliance on gloss annotations which underpin other state-of-the-art approaches, thereby removing future need for expensive curated datasets

Is Quantum Mechanics An Island In Theoryspace?

This recreational paper investigates what happens if we change quantum mechanics in several ways. The main results are as follows. First, if we replace the 2-norm by some other p-norm, then there are no nontrivial norm-preserving linear maps. Second, if we relax the demand that norm be preserved, we end up with a theory that allows rapid solution of PP-complete problems (as well as superluminal signalling). And third, if we restrict amplitudes to be real, we run into a difficulty much simpler than the usual one based on parameter-counting of mixed states.Comment: 9 pages, minor correction

A rule-based translation from written Spanish to Spanish Sign Language glosses

This is the author’s version of a work that was accepted for publication in Computer Speech and Language. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Speech and Language, 28, 3 (2015) DOI: 10.1016/j.csl.2013.10.003One of the aims of Assistive Technologies is to help people with disabilities to communicate with others and to provide means of access to information. As an aid to Deaf people, we present in this work a production-quality rule-based machine system for translating from Spanish to Spanish Sign Language (LSE) glosses, which is a necessary precursor to building a full machine translation system that eventually produces animation output. The system implements a transfer-based architecture from the syntactic functions of dependency analyses. A sketch of LSE is also presented. Several topics regarding translation to sign languages are addressed: the lexical gap, the bootstrapping of a bilingual lexicon, the generation of word order for topic-oriented languages, and the treatment of classifier predicates and classifier names. The system has been evaluated with an open-domain testbed, reporting a 0.30 BLEU (BiLingual Evaluation Understudy) and 42% TER (Translation Error Rate). These results show consistent improvements over a statistical machine translation baseline, and some improvements over the same system preserving the word order in the source sentence. Finally, the linguistic analysis of errors has identified some differences due to a certain degree of structural variation in LSE

Software engineering and middleware: a roadmap (Invited talk)

The construction of a large class of distributed systems can be simplified by leveraging middleware, which is layered between network operating systems and application components. Middleware resolves heterogeneity and facilitates communication and coordination of distributed components. Existing middleware products enable software engineers to build systems that are distributed across a local-area network. State-of-the-art middleware research aims to push this boundary towards Internet-scale distribution, adaptive and reconfigurable middleware and middleware for dependable and wireless systems. The challenge for software engineering research is to devise notations, techniques, methods and tools for distributed system construction that systematically build and exploit the capabilities that middleware deliver

Of Mammies, Minstrels, and Machines: Movement-Image Automaticity and the Impossible Conditions of Black Humanity

This thesis argues that the GIF, as an underexplored analytical vertex within the broader matrix of media ecologies, should be understood as a generative nodal point in the American system of racialized violence. Thought in relation to its medium specificity, the GIF\u27s materiality, particularly its capacity for infinite looping, is critically interrogated for its potential to amplify the circuitry of dominating racialization that felicitously condition the GIF\u27s circulation. I open my argument with focus on a subset of the GIF genre known as the reaction GIF, which, in its frequently racialized form, is situated within the interconnected genealogies of the figures of the mammy, the minstrel, and the machine. The reaction GIF is shown as a contemporary iteration of minstrel performance, known as blackface minstrelsy, that is deeply imbricated with the subordinating racialization of Black women. I demonstrate that the violent genealogies of mammy, minstrel, and machine facilitate the machinic transfiguration of Black women made into GIF content, a process of making-machine of the Black woman subject. Making-machine is the site of ontological capture the racialized reaction GIF institutes, and those Black women caught within its digital field become the inhuman iconography of the medium\u27s motif. To substantiate this account of the racializing properties of the GIF, the text engages the GIF at the level of its mediatic specificity and through questions of affective labor and its expropriation. I contend that the mediatic properties of the GIF are central to its modulating brokerage of affect, and it is this capacity to disperse infinitely differentiated affective impulses that underpins the racialized reaction GIF\u27s making-machine of Black women subjects

Machine Ethics, Ethics for Machines: Context-Based Modeling for Machines Making Ethical Decisions

Machine ethics is an emerging, interdisciplinary field that focuses on if – and if so, how – machines can make ethical decisions autonomously. Through a close study of two positions on whether or not machines can be moral agents, this project sheds light on a clash of assumptions that is keeping the field of machine ethics in limbo. After making this clash of assumptions clear, I raise two questions which get at the scope of machine ethics itself: 1) What makes ethical decision-making different from other kinds of decision-making? 2) To what extent can machines engage with ethics and make ethical decisions? I address the first question by arguing that ethics is distinct because it requires the ability to understand and participate in human conventions. I address the second question by arguing that ethics has always been informed by our humanity, but machine ethics is an opportunity to expand our understanding of ethics so that machines can engage with it insofar as they are machines. This project aims to contribute to machine ethics by proposing a major shift in perspective, from a focus on human abilities to a focus on machines and their own radically novel abilities