Speaker Recognition In Noisy Conditions With Limited Training Data

In this paper we present a novel method for performing speaker recognition with very limited training data and in the presence of background noise. Similarity-based speaker recognition is considered so that speaker models can be created with limited training speech data. The proposed similarity is a form of cosine similarity used as a distance measure between speech feature vectors. Each speech frame is modelled using subband features, and into this framework, multicondition training and optimal feature selection are introduced, making the system capable of performing speaker recognition in the presence of realistic, time-varying noise, which is unknown during training. Speaker identi?cation experiments were carried out using the SPIDRE database. The performance of the proposed new system for noise compensation is compared to that of an oracle model; the speaker identi?cation accuracy for clean speech by the new system trained with limited training data is compared to that of a GMM trained with several minutes of speech. Both comparisons have demonstrated the effectiveness of the new model. Finally, experiments were carried out to test the new model for speaker identi?cation given limited training data and with differing levels and types of realistic background noise. The results have demonstrated the robustness of the new system.

Effectiveness of child protection training for pre-service early childhood educators

International evidence confirms that early childhood educators can enter professional practice unprepared for child protection due to inadequate pre-service preparation. This paper makes an original contribution by using the Child Protection Questionnaire for Educators (CPQE) to examine the pre- and post- intervention child maltreatment and protection knowledge of early childhood and primary teaching students. While students’ knowledge increases significantly after participating in a child protection training programme, Pastoral Pathways, as part of their undergraduate study, post-intervention scores vary between groups. The study provides evidence of programme effectiveness and future training needs of pre-service educators. Findings are relevant to teacher educators and child care training providers in relation to programme content development and evidencing knowledge and skills acquisition.

Training-induced modifications of corticospinal reactivity in severely affected stroke survivors

When permitted access to the appropriate forms of rehabilitation, many severely affected stroke survivors demonstrate a capacity for upper limb functional recovery well in excess of that formerly considered possible. Yet, the mechanisms through which improvements in arm function occur in such profoundly impaired individuals remain poorly understood. An exploratory study was undertaken to investigate the capacity for brain plasticity and functional adaptation, in response to 12-h training of reaching using the SMART Arm device, in a group of severely affected stroke survivors with chronic upper limb paresis. Twenty-eight stroke survivors were enroled. Eleven healthy adults provided normative data. To assess the integrity of ipsilateral and contralateral corticospinal pathways, transcranial magnetic stimulation was applied to evoke responses in triceps brachii during an elbow extension task. When present, contralateral motor-evoked potentials (MEPs) were delayed and reduced in amplitude compared to those obtained in healthy adults. Following training, contralateral responses were more prevalent and their average onset latency was reduced. There were no reliable changes in ipsilateral MEPs. Stroke survivors who exhibited contralateral MEPs prior to training achieved higher levels of arm function and exhibited greater improvements in performance than those who did not initially exhibit contralateral responses. Furthermore, decreases in the onset latency of contralateral MEPs were positively related to improvements in arm function. Our findings demonstrate that when severely impaired stroke survivors are provided with an appropriate rehabilitation modality, modifications of corticospinal reactivity occur in association with sustained improvements in upper limb function.

Superimposed vibration confers no additional benefit compared with resistance training alone

Eighteen participants (22-43 years) were randomly allocated to one of two groups: resistance training combined with vibration (VIB; five males, four females) or resistance training alone (CON; five males, four females). Each participant trained three sessions per week (three sets of 10 seated calf raises against a load, which was increased progressively from 75% of one repetition maximum (1RM) to 90% 1RM for 4 weeks. For the VIB group, a vibratory stimulus (30 Hz, 2.5 mm amplitude) was applied to the soles of the feet by a vibration platform. The two groups did not differ significantly with respect to the total amount of work performed during training. Both groups showed a significant increase in maximum voluntary contraction and 1RM (P

Development of a multi-media book for clinical supervision training in undergraduate nursing

There is an increased interest in higher education in the use of e-learning resources for students. This can be attributed to many factors including, the availability of advanced technology systems, a growing student population that is technology focused, financial implications and the recruitment of international students. However, the introduction of technology and e-learning into teaching has given rise to issues regarding quality and quantity of educational practice . The challenge now is for educationalists is to deliver an optimal learning experience that is effective and appropriate for students’ learning needs.

SVM Training Phase Reduction Using Dataset Feature Filtering for Malware Detection

N-gram analysis is an approach that investigates the structure of a program using bytes, characters, or text strings. A key issue with N-gram analysis is feature selection amidst the explosion of features that occurs when N is increased. The experiments within this paper represent programs as operational code (opcode) density histograms gained through dynamic analysis. A support vector machine is used to create a reference model, which is used to evaluate two methods of feature reduction, which are 'area of intersect' and 'subspace analysis using eigenvectors.' The findings show that the relationships between features are complex and simple statistics filtering approaches do not provide a viable approach. However, eigenvector subspace analysis produces a suitable filter.