Theories of developmental dyslexia: Insights from a multiple case study of dyslexic adults

A multiple case study was conducted in order to assess three leading theories of developmental dyslexia: the phonological, the magnocellular (auditory and visual) and the cerebellar theories. Sixteen dyslexic and 16 control university students were administered a full battery of psychometric, phonological, auditory, visual and cerebellar tests. Individual data reveal that all 16 dyslexics suffer from a phonological deficit, 10 from an auditory deficit, 4 from a motor deficit, and 2 from a visual magnocellular deficit. Results suggest that a phonological deficit can appear in the absence of any other sensory or motor disorder, and is sufficient to cause a literacy impairment, as demonstrated by 5 of the dyslexics. Auditory disorders, when present, aggravate the phonological deficit, hence the literacy impairment. However, auditory deficits cannot be characterised simply as rapid auditory processing problems, as would be predicted by the magnocellular theory. Nor are they restricted to speech. Contrary to the cerebellar theory, we find little support for the notion that motor impairments, when found, have a cerebellar origin, or reflect an automaticity deficit. Overall, the present data support the phonological theory of dyslexia, while acknowledging the presence of additional sensory and motor disorders in certain individuals

Audio impairment recognition using a correlation-based feature representation

Audio impairment recognition is based on finding noise in audio files and categorising the impairment type. Recently, significant performance improvement has been obtained thanks to the usage of advanced deep learning models. However, feature robustness is still an unresolved issue and it is one of the main reasons why we need powerful deep learning architectures. In the presence of a variety of musical styles, hand-crafted features are less efficient in capturing audio degradation characteristics and they are prone to failure when recognising audio impairments and could mistakenly learn musical concepts rather than impairment types. In this paper, we propose a new representation of hand-crafted features that is based on the correlation of feature pairs. We experimentally compare the proposed correlation-based feature representation with a typical raw feature representation used in machine learning and we show superior performance in terms of compact feature dimensionality and improved computational speed in the test stage whilst achieving comparable accuracy

A Method for Analysis of Patient Speech in Dialogue for Dementia Detection

We present an approach to automatic detection of Alzheimer's type dementia based on characteristics of spontaneous spoken language dialogue consisting of interviews recorded in natural settings. The proposed method employs additive logistic regression (a machine learning boosting method) on content-free features extracted from dialogical interaction to build a predictive model. The model training data consisted of 21 dialogues between patients with Alzheimer's and interviewers, and 17 dialogues between patients with other health conditions and interviewers. Features analysed included speech rate, turn-taking patterns and other speech parameters. Despite relying solely on content-free features, our method obtains overall accuracy of 86.5\%, a result comparable to those of state-of-the-art methods that employ more complex lexical, syntactic and semantic features. While further investigation is needed, the fact that we were able to obtain promising results using only features that can be easily extracted from spontaneous dialogues suggests the possibility of designing non-invasive and low-cost mental health monitoring tools for use at scale.Comment: 8 pages, Resources and ProcessIng of linguistic, paralinguistic and extra-linguistic Data from people with various forms of cognitive impairment, LREC 201

Linking metacognition and mindreading: Evidence from autism and dual-task investigations

Questions of how we know our own and other minds, and whether metacognition and mindreading rely on the same processes, are longstanding in psychology and philosophy. In Experiment 1, children/adolescents with autism (who tend to show attenuated mindreading) showed significantly lower accuracy on an explicit metacognition task than neurotypical children/adolescents, but not on an allegedly metacognitive implicit one. In Experiment 2, neurotypical adults completed these tasks in a single-task condition, or a dual-task condition that required concurrent completion of a secondary task that tapped mindreading. Metacognitive accuracy was significantly diminished by the dual-mindreading-task on the explicit task, but not the implicit task. In Experiment 3, we included additional dual-tasks to rule out the possibility that any secondary task (regardless of whether it required mindreading) would diminish metacognitive accuracy. Finally, in both experiments 1 and 2, metacognitive accuracy on the explicit task, but not the implicit task, was associated significantly with performance on a measure of mindreading ability. These results suggest that explicit metacognitive tasks (used frequently to measure metacognition in humans) share metarepresentational processing resources with mindreading, whereas implicit tasks (which are claimed by some comparative psychologists to measure metacognition in non-human animals) do not

Evaluation of a context-aware voice interface for Ambient Assisted Living: qualitative user study vs. quantitative system evaluation

International audienceThis paper presents an experiment with seniors and people with visual impairment in a voice-controlled smart home using the SWEET-HOME system. The experiment shows some weaknesses in automatic speech recognition which must be addressed, as well as the need of better adaptation to the user and the environment. Indeed, users were disturbed by the rigid structure of the grammar and were eager to adapt it to their own preferences. Surprisingly, while no humanoid aspect was introduced in the system, the senior participants were inclined to embody the system. Despite these aspects to improve, the system has been favourably assessed as diminishing most participant fears related to the loss of autonomy

Advanced concept of voice communication server on embedded platform

The paper deals with a design of an embedded Voice communication server which was developed within the scope of the BESIP project (Bright Embedded Solution for IP Telephony). The project brings a modular architecture with additional functionality such as a speech quality monitoring and a protection against security threats.The speech quality assessment is carried out in a simplified computational E-model and we implemented our proposal into the BESIP as an optional component. In the security module. We applied a standard approach to the intrusion detection and protection and in addition to the mentioned modules we come up with an idea of unified configuration based on the NETCONF protocol. We implemented ntegrated the complex support of NETCONF configuration protoco into OpenWRT and our modifications were accepted by OpenWRT community. The paper describes the inidvidual modules, their features and entire BESIP concept.Scopus892b23322