Strongly Incremental Repair Detection

Hough is supported by the DUEL project, financially supported by the Agence Nationale de la Research (grant number ANR-13-FRAL-0001) and the Deutsche Forschungsgemainschaft. Much of the work was carried out with support from an EPSRC DTA scholarship at Queen Mary University of London. Purver is partly supported by ConCreTe: the project ConCreTe acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET grant number 61173

Strongly Incremental Repair Detection

Hough J, Purver M. Strongly Incremental Repair Detection. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Doha, Qatar: ACL; 2014: 78-89.We present STIR (STrongly Incremental Repair detection), a system that detects speech repairs and edit terms on transcripts incrementally with minimal latency. STIR uses information-theoretic measures from n-gram models as its principal decision features in a pipeline of classifiers detecting the different stages of repairs. Results on the Switchboard disfluency tagged corpus show utterance-final accuracy on a par with state-of-the-art incremental repair detection methods, but with better incremental accuracy, faster time-to-detection and less computational overhead. We evaluate its performance using incremental metrics and propose new repair processing evaluation standards

Increase Apparent Public Speaking Fluency By Speech Augmentation

Fluent and confident speech is desirable to every speaker. But professional speech delivering requires a great deal of experience and practice. In this paper, we propose a speech stream manipulation system which can help non-professional speakers to produce fluent, professional-like speech content, in turn contributing towards better listener engagement and comprehension. We propose to achieve this task by manipulating the disfluencies in human speech, like the sounds 'uh' and 'um', the filler words and awkward long silences. Given any unrehearsed speech we segment and silence the filled pauses and doctor the duration of imposed silence as well as other long pauses ('disfluent') by a predictive model learned using professional speech dataset. Finally, we output a audio stream in which speaker sounds more fluent, confident and practiced compared to the original speech he/she recorded. According to our quantitative evaluation, we significantly increase the fluency of speech by reducing rate of pauses and fillers

Miscommunication in Doctor-Patient Communication

The effectiveness of medical treatment depends on the quality of the patient–clinician relationship. It has been proposed that this depends on the extent to which the patient and clinician build a shared understanding of illness and treatment. Here, we use the tools of conversation analysis (CA) to explore this idea in the context of psychiatric consultations. The CA “repair” framework provides an analysis of the processes people use to deal with problems in speaking, hearing, and understanding. These problems are especially critical in the treatment of psychosis where patients and health care professionals need to communicate about the disputed meaning of hallucinations and delusion. Patients do not feel understood, they are frequently non‐adherent with treatment, and many have poor outcomes. We present an overview of two studies focusing on the role of repair as a mechanism for producing and clarifying meaning in psychiatrist–patient communication and its association with treatment outcomes. The first study shows patient clarification or repair of psychiatrists’ talk is associated with better patient adherence to treatment. The second study shows that training which emphasizes the importance of building an understanding of patients’ psychotic experiences increases psychiatrists’ self‐repair. We propose that psychiatrists are working harder to make their talk understandable and acceptable to the patient by taking the patient's perspective into account. We conclude that these findings provide evidence that repair is an important mechanism for building shared understanding in doctor–patient communication and contributes to better therapeutic relationships and treatment adherence. The conversation analytic account of repair is currently the most sophisticated empirical model for analyzing how people construct shared meaning and understanding. Repair appears to reflect greater commitment to and engagement in communication and improve both the quality and outcomes of communication. Reducing potential miscommunication between psychiatrists and their patients with psychosis is a low‐cost means of enhancing treatment from both the psychiatrist and patient perspective. Given that misunderstanding and miscommunication are particularly problematic in psychosis, this is critical for improving the longer term outcomes of treatment for these patients who often have poor relationships with psychiatrists and health care services more widely

Chaining Test Cases for Reactive System Testing (extended version)

Testing of synchronous reactive systems is challenging because long input sequences are often needed to drive them into a state at which a desired feature can be tested. This is particularly problematic in on-target testing, where a system is tested in its real-life application environment and the time required for resetting is high. This paper presents an approach to discovering a test case chain---a single software execution that covers a group of test goals and minimises overall test execution time. Our technique targets the scenario in which test goals for the requirements are given as safety properties. We give conditions for the existence and minimality of a single test case chain and minimise the number of test chains if a single test chain is infeasible. We report experimental results with a prototype tool for C code generated from Simulink models and compare it to state-of-the-art test suite generators.Comment: extended version of paper published at ICTSS'1

Virtual RTCP: A Case Study of Monitoring and Repair for UDP-based IPTV Systems

IPTV systems have seen widespread deployment, but often lack robust mechanisms for monitoring the quality of experience. This makes it difficult for network operators to ensure that their services match the quality of traditional broadcast TV systems, leading to consumer dissatisfaction. We present a case study of virtual RTCP, a new framework for reception quality monitoring and reporting for UDP-encapsulated MPEG video delivered over IP multicast. We show that this allows incremental deployment of reporting infrastructure, coupled with effective retransmission-based packet loss repair