BOLTZMANN MACHINES FOR SPEECH RECOGNITION.

Boltzmann machines offer a new and exciting approach to automatic speech recognition, and provide a rigorous mathematical formalism for parallel computing arrays. In this paper we briefly summarize Boltzmann machine theory, and present results showing their ability to recognize both static and time-varying speech patterns. A machine with 2000 units was able to distinguish between the 11 steady-state vowels in English with an accuracy of 85%. The stability of the learning algorithm and methods of preprocessing and coding speech data before feeding it to the machine are also discussed. A new type of unit called a carry input unit, which involves a type of state-feedback, was developed for the processing of time-varying patterns and this was tested on a few short sentences. Use is made of the implications of recent work into associative memory, and the modelling of neural arrays to suggest a good configuration of Boltzmann machines for this sort of pattern recognition.

Analysis and performance assessment of 6-pulse inverter-fed 3-phase and 6-phase induction machines

The paper describes a model for a 6-phase induction motor driven by an inverter operating in a 6-pulse (square wave) mode. The model is implemented and performance, in terms of torque, current, efficiency and pulsating torque, compared to the performance of a 3-phase motor (both sine and 6-pulse supplied). The models are verified experimentally, in particular the efficiency performance, and it is illustrated that the improvement in inverter efficiency when in 6-pulse operating mode may improve the performance of the overall system. © 2005 IEEE.

Duty cycle and modelling considerations in three-phase induction motor drives for washing machines

Three-phase induction motors offer significant advantages over commutator motors in some domestic appliances. Models for wide speed range three-phase induction motors for use in a horizontal axis washing machine have been developed using the MEGA finite element package with an external formulation for calculating iron losses. Motor loss predictions have been verified using a novel high accuracy calorimeter. Good agreement has been observed over a wide speed range at different loadings. The model is used to predict motor temperature rise under typical washing machine loading conditions to ensure its limiting temperature is not exceeded and enables alternative designs to be investigated without recourse to physical prototypes. © 2005 IEEE.

Modeling and electrical measurement of transport AC loss in HTS-based superconducting coils for electric machines

AC loss can be a significant problem for any applications that utilize or produce an AC current or magnetic field, such as an electric machine. The authors are currently investigating the electromagnetic properties of high temperature superconductors with a particular focus on the AC loss in coils made from YBCO superconductors. In this paper, a 2D finite element model based on the H formulation is introduced. The model is then used to calculate the transport AC loss using both a bulk approximation and modeling the individual turns in a racetrack-shaped coil. The coil model is based on the superconducting stator coils used in the University of Cambridge EPEC Superconductivity Group's superconducting permanent magnet synchronous motor design. The transport AC loss of a stator coil is measured using an electrical method based on inductive compensation using a variable mutual inductance. The simulated results are compared with the experimental results, verifying the validity of the model, and ways to improve the accuracy of the model are discussed. © 2010 IEEE.

Structured precision modelling with Cholesky basis superposition for speech recognition

Structured precision modelling is an important approach to improve the intra-frame correlation modelling of the standard HMM, where Gaussian mixture model with diagonal covariance are used. Previous work has all been focused on direct structured representation of the precision matrices. In this paper, a new framework is proposed, where the structure of the Cholesky square root of the precision matrix is investigated, referred to as Cholesky Basis Superposition (CBS). Each Cholesky matrix associated with a particular Gaussian distribution is represented as a linear combination of a set of Gaussian independent basis upper-triangular matrices. Efficient optimization methods are derived for both combination weights and basis matrices. Experiments on a Chinese dictation task showed that the proposed approach can significantly outperformed the direct structured precision modelling with similar number of parameters as well as full covariance modelling. © 2011 IEEE.

The double dance of agency: a socio-theoretic account of how machines and humans interact

The nature of the relationship between information technology (IT) and organizations has been a long-standing debate in the Information Systems literature. Does IT shape organizations, or do people in organisations control how IT is used? To formulate the question a little differently: does agency (the capacity to make a difference) lie predominantly with machines (computer systems) or humans (organisational actors)? Many proposals for a middle way between the extremes of technological and social determinism have been put advanced; in recent years researchers oriented towards social theories have focused on structuration theory and (lately) actor network theory. These two theories, however, adopt different and incompatible views of agency. Thus, structuration theory sees agency as exclusively a property of humans, whereas the principle of general symmetry in actor network theory implies that machines may also be agents. Drawing on critiques of both structuration theory and actor network theory, this paper develops a theoretical account of the interaction between human and machine agency: the double dance of agency. The account seeks to contribute to theorisation of the relationship between technology and organisation by recognizing both the different character of human and machine agency, and the emergent properties of their interplay.