Herbert Reininger

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This paper investigates two methods to define a distance measure between any pair of Hidden Markov Models (HMM). The first one is the geometricaly motivated euclidean distance which solely incorporates the feature probabilities. The second measure is the Kulback-Liebler distance which is based on the discriminating power of the probability measure on the(More)
In this paper we summarize the experiences gained from a field trial of a speaker verification system. In the test implementation access to two rooms at the University of Frankfurt had been controlled by a speaker verification system. The paper is organized as follows: Firstly, we will describe the system concepts and implementation issues. Secondly,(More)
Recurrent Neural Networks (RNN) provide a solution for low cost Speech Recognition Systems (SRS) in mass products or in products with energetic constraints if their inherent parallelism could be exploited in a hardware realization. Actually, the computational complexity of SRS based on Fully Recurrent Neural Networks (FRNN), e.g. the large number of(More)
The combination of a model of auditory perception PEMO as feature extractor and of a Locally Recurrent Neural Network LRNN as classiier yields promising ASR results in noise. Our study focuses on the interplay b e t w een both techniques and their ability t o complement each other in the task of robust speech recognition. We performed recognition(More)
In this paper we present a robust speaker independent speech recognition system consisting of a feature extraction based on a model of the auditory periphery, and a Locally Recurrent Neural Network for scoring of the derived feature vectors. A number of recognition experiments were carried out to investigate the robustness of this combination against(More)
Biometric speaker verification deals with the recognition of voice and speech features to reliably identify a user and to offer him a comfortable alternative to knowledge-based authentication methods like passwords. As more and more personal data is saved on smartphones and other mobile devices, their security is in the focus of recent applications.(More)