Exploiting Chinese character models to improve speech recognition performance

The Chinese language is based on characters which are syllabic in nature. Since languages have syllabotactic rules which govern the construction of syllables and their allowed sequences, Chinese character sequence models can be used as a first level approximation of allowed syllable sequences. N-gram character sequence models were trained on 4.3 billion characters. Characters are used as a first level recognition unit with multiple pronunciations per character. For comparison the CU-HTK Mandarin word based system was used to recognize words which were then converted to character sequences. The character only system error rates for one best recognition were slightly worse than word based character recognition. However combining the two systems using log-linear combination gives better results than either system separately. An equally weighted combination gave consistent CER gains of 0.1-0.2% absolute over the word based standard system. Copyright © 2009 ISCA.

Probabilistic inference for fast learning in control

A novel framework is provided for very fast model-based reinforcement learning in continuous state and action spaces. It requires probabilistic models that explicitly characterize their levels of condence. Within the framework, exible, non-parametric models are used to describe the world based on previously collected experience. It demonstrates learning on the cart-pole problem in a setting where very limited prior knowledge about the task has been provided. Learning progressed rapidly, and a good policy found after only a small number of iterations.

Principles of sensorimotor learning.

The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities - whether it is snowboarding or ballroom dancing - but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved.

Principles of sensorimotor learning

The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities-whether it is snowboarding or ballroom dancing-but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved. © 2011 Macmillan Publishers Limited. All rights reserved.

Graduate education for leadership and organisational change in sustainable development

This paper reflects on the motivation, method and effectiveness of teaching leadership and organisational change to graduate engineers. Delivering progress towards sustainable development requires engineers who are aware of pressing global issues (such as resource depletion, climate change, social inequity and an interdependent economy) since it is they who deliver the goods and services that underpin society within these constraints. They also must understand how to implement change in the organisations within which they will work. In recognition of this fact the Cambridge University MPhil in Engineering for Sustainable Development has focussed on educating engineers to become effective change agents in their professional field with the confidence to challenge orthodoxy in adopting traditional engineering solutions. This paper reflects on ten years of delivering a special module to review how teaching change management and leadership aspects of the programme have evolved and progressed over that time. As the students who embark on this professional practice have often extensive experience as practising engineers and scientists, many have already learned the limitations of their technical background when solving complex problems. Students often join the course recognising their need to broaden their knowledge of relevant cross-disciplinary skills. The programme offers an opportunity for these early to mid-career engineers to explore an ethical and value-based approach to bringing about effective change in their particular sectors and organisations. This is achieved through action learning assignments in combination with reflections on the theory of change to enable students to equip themselves with tools that help them to be effective in making their professional and personal life choices. This paper draws on feedback gathered from students during their participation on the programme and augments this with alumni reflections gathered some years after their graduation. These professionals are able to look back on their experience of the taught components and reflect on how they have been able to apply this key learning in their subsequent careers. Copyright © 2012 September.

Slowness and sparseness lead to place, head-direction, and spatial-view cells.

We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. The model comprises a hierarchy of Slow Feature Analysis (SFA) nodes, which were recently shown to reproduce many properties of complex cells in the early visual system []. The system extracts a distributed grid-like representation of position and orientation, which is transcoded into a localized place-field, head-direction, or view representation, by sparse coding. The type of cells that develops depends solely on the relevant input statistics, i.e., the movement pattern of the simulated animal. The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer.

Digital radio distribution system over multiple cabling types

This paper demonstrates a novel digital radio distribution system able to transmit not only over optical fibres and coaxial cables but also over twisted pair cables. The digitised RF signal is compressed for maximum transmission efficiency in a way that allows for integral self-learning algorithms to be introduced for multi-service applications. © 2013 IEEE.