Cognitive and bodily selves: how do they interact following brain lesion?

Dualism has long distinguished between the mental and the body experiences. Probing the structure and organisation of the self traditionally calls for a distinction between these two sides of the self coin. It is far beyond the scope of this chapter to address these philosophical issues, and our starting point will be the simple distinction between reflective processes involved in the elaboration of body image, self awareness and self-recognition (i.e. ‘the self’) and the sensori-motor dialogues involved in action control, reactions and automatisms (i.e. ‘the body’ schema). This oversimplification does not take into account the complex interactions taking place between these two levels of description, but our initial aim will be to distinguish between them, before addressing the question of their interactions. Cognitive and sensori-motor processes have frequently been distinguished (review: Rossetti and Revonsuo 2000), and it may be proposed that a similar dissociation can be put forward, a priori, between a central representation of self and a bodily representation corresponding to body schema (Figure 1)

Adaptation by normal listeners to upward spectral shifts of speech: Implications for cochlear implants

Multi-channel cochlear implants typically present spectral information to the wrong ''place'' in the auditory nerve array, because electrodes can only be inserted partway into the cochlea. Although such spectral shifts are known to cause large immediate decrements in performance in simulations, the extent to which listeners can adapt to such shifts has yet to be investigated. Here, the effects of a four-channel implant in normal listeners have been simulated, and performance tested with unshifted spectral information and with the equivalent of a 6.5-mm basalward shift on the basilar membrane (1.3-2.9 octaves, depending on frequency). As expected, the unshifted simulation led to relatively high levels of mean performance (e;g., 64% of words in sentences correctly identified) whereas the shifted simulation led to very poor results (e.g., 1% of words). However, after just nine 20-min sessions of connected discourse tracking with the shifted simulation, performance improved significantly for the identification of intervocalic consonants, medial vowels in monosyllables, and words in sentences (30% of words). Also, listeners were able to track connected discourse of shifted signals without lipreading at rates up to 40 words per minute. Although we do not know if complete adaptation to the shifted signals is possible, it is clear that short-term experiments seriously exaggerate the long-term consequences of such spectral shifts. (C) 1999 Acoustical Society of America. [S0001-4966(99)02012-3]

The LEA's perspective of change : the case for directed development

Pages numbered 1-40Bibliography: p. 37-40Supported in part by the National Institute of Education under contract no. NIE-400-81-003

Improvements to deep convolutional neural networks for LVCSR

Deep Convolutional Neural Networks (CNNs) are more powerful than Deep Neural Networks (DNN), as they are able to better reduce spectral variation in the input signal. This has also been confirmed experimentally, with CNNs showing improvements in word error rate (WER) between 4-12% relative compared to DNNs across a variety of LVCSR tasks. In this paper, we describe different methods to further improve CNN performance. First, we conduct a deep analysis comparing limited weight sharing and full weight sharing with state-of-the-art features. Second, we apply various pooling strategies that have shown improvements in computer vision to an LVCSR speech task. Third, we introduce a method to effectively incorporate speaker adaptation, namely fMLLR, into log-mel features. Fourth, we introduce an effective strategy to use dropout during Hessian-free sequence training. We find that with these improvements, particularly with fMLLR and dropout, we are able to achieve an additional 2-3% relative improvement in WER on a 50-hour Broadcast News task over our previous best CNN baseline. On a larger 400-hour BN task, we find an additional 4-5% relative improvement over our previous best CNN baseline.Comment: 6 pages, 1 figur

Unsupervised Adaptation for Synthetic-to-Real Handwritten Word Recognition

Handwritten Text Recognition (HTR) is still a challenging problem because it must deal with two important difficulties: the variability among writing styles, and the scarcity of labelled data. To alleviate such problems, synthetic data generation and data augmentation are typically used to train HTR systems. However, training with such data produces encouraging but still inaccurate transcriptions in real words. In this paper, we propose an unsupervised writer adaptation approach that is able to automatically adjust a generic handwritten word recognizer, fully trained with synthetic fonts, towards a new incoming writer. We have experimentally validated our proposal using five different datasets, covering several challenges (i) the document source: modern and historic samples, which may involve paper degradation problems; (ii) different handwriting styles: single and multiple writer collections; and (iii) language, which involves different character combinations. Across these challenging collections, we show that our system is able to maintain its performance, thus, it provides a practical and generic approach to deal with new document collections without requiring any expensive and tedious manual annotation step.Comment: Accepted to WACV 202

The Performance of Dialysis Care: Routinization and Adaptation on the Floor

Previous studies of communication in dialysis centers primarily focused on communication between nurses and patients. In this study, ethnographic methods were used to explore the dominant communication performances enacted by dialysis staff members, including registered nurses, patient care technicians, technical aides, a social worker, and a dietitian. Findings suggest a dialectic between extreme routinization of care and continual adaptation. The dominant routine involved repeating the same preparation, treatment, and discharge process 3 shifts per day, thrice weekly for each patient. At the same time, near-constant adjustments to scheduling, coordination of tasks, and problem solving were needed to maintain the performance of repetition. The balancing of this dialectic has significant implications for new staff training and socialization, understanding the role of technology and routine in dialysis and in health care systems more generally, and in further theorizing the role of unbounded communication interactions in health care