Searching for authors named "Soren Kamaric Riis" – sorted by Relevance.
7 documents found, showing 1 through 7.
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Joint Estimation of Parameters in Hidden Neural Networks
- …It has been proven by several authors that hybrids of Hidden Markov Models (HMM) and Neural Networks (NN) yield good performance in speech recognition. However, in many of the current hybrids the HMM and neural networks are trained separately and only combined during decoding. In this paper we propo…
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Adaptive Transition Bias for Robust Low Complexity Speech Recognition
- … with the University of Sheffield, UK. Email: k.koumpis@(email omitted); Konstantinos Koumpis and Søren Kamaric Riis…
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Hidden Neural Networks: A Framework For HMM/NN Hybrids
- …This paper presents a general framework for hybrids of Hidden Markov models (HMM) and neural networks (NN). In the new framework called Hidden Neural Networks (HNN) the usual HMM probability parameters are replaced by neural network outputs. To ensure a probabilistic interpretation the HNN is normal…
- Cited by 10 (4 self) – Add To MetaCart
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Prediction of Beta Sheets in Proteins
- …Most current methods for prediction of protein secondary structure use a small window of the protein sequence to predict the structure of the central amino acid. We describe a new method for prediction of the non-local structure called fi-sheet, which consists of two or more fi-strands that are conn…
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Improving Prediction of Protein Secondary Structure using Structured Neural Networks and Multiple Sequence Alignments
- …The prediction of protein secondary structure by use of carefully structured neural networks and multiple sequence alignments has been investigated. Separate networks are used for predicting the three secondary structures ff-helix, fi-strand and coil. The networks are designed using a priori knowled…
- Cited by 44 (4 self) – Add To MetaCart
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Hidden Markov Models and Neural Networks for Speech Recognition
- …The Hidden Markov Model (HMMs) is one of the most successful modeling approaches for acoustic events in speech recognition, and more recently it has proven useful for several problems in biological sequence analysis. Although the HMM is good at capturing the temporal nature of processes such as spee…
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Hidden Neural Networks: Application To Speech Recognition
- …In this paper we evaluate the Hidden Neural Network HMM/NN hybrid presented at last years ICASSP on two speech recognition benchmark tasks; 1) task independent isolated word recognition on the PHONEBOOK database, and 2) recognition of broad phoneme classes in continuous speech from the TIMIT databas…
- Cited by 2 (1 self) – Add To MetaCart
Showing 1 through 7.
