Meinhard Ullrich

Method of speech recognition

In a method in which an information unit (4) enabling a speech input is stored on a server (5) and can be retrieved by a client (1, 2, 3) and in which the client can be coupled to one or more speech recognizers (7, 8, 9) through a communications network (6), the information unit (4) is assigned additional information (12) which is provided for determining a combination of a client (1, 2, 3) for recognizing an uttered speech signal and at least one of the speech recognizers (7, 8, 9), to dynamically assign the speech recognizers (7, 8, 9) in a communications network (6) to the information units (4) and thus ensure an acceptable processing time for the recognition of a speech input with a high recognition quality.

A bottom-up approach for handling unseen triphones in large vocabulary continuous speech recognition

Presents an extension of bottom-up state-tying towards improved handling of unseen triphones. As opposed to the usual backing-off to diphones and monophones, the current method aims at finding a triphone model that has proven to exhibit some similarity with the unseen triphone. It is based on a probabilistic mapping of unseen contexts to clusters of triphone states observed in the training data. This algorithm has been applied to dictation tasks for three languages with vocabulary sizes ranging from 20k to 64k. The results compare favorably with those obtained using standard back-off rules. This technique also offers an alternative to top-down decision-tree procedures which are frequently used, especially for their generalization capabilities.

An adaptive method to learn the compatibility matrix for microcellular systems

In a micro-cellular system, radio propagation prediction may be replaced by statistical analysis of the running system, as far as the distribution of the radio resource between cells is concerned. To this end, interference level and channel usage are sampled and correlated. As a result, the estimation of the compatibility of channels being used at different cell sites can be updated and used for a revised channel assignment. This approach may be seen as a special case of the more general idea of self-optimising networks. The feasibility of the method has been studied by simulations.<<ETX>>

Learning the compatibility matrix for adaptive resource management in cellular radio networks

To satisfy the growing demand for mobile communications micro-cellular systems are expected to be introduced in the near future. For these, effective procedures not only for channel allocation but also for load balancing and call admission control still have to be developed. Here, the knowledge of the actual interference relations between radio cells is a key issue for both the more traditional channelized systems and the recently proposed spread spectrum techniques. Realizing that the interference relations among the cells are only slowly varying, the authors generalize the existing local and short term approaches to interference detection by including a memory trace in the evaluation procedure. A compatibility matrix for the cells is learned by statistically correlating carrier and interference power levels with call activities. In this paper, the overall system design is presented along with the detailed description of the learning procedure which is thought of as both an integrated component of future radio network management systems as well as a possible enhancement of already existing radio network planning methods. Simulations show that the adaptive strategy offers a considerable capacity increase that results from an increased spectrum efficiency.