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The frame rate of the observation sequence in distributed speech recognition applications may be reduced to suit a resource-limited front-end device. In order to use models trained using full-frame-rate data in the recognition of reduced frame-rate (RFR) data, we propose a method for adapting the transition probabilities of hidden Markov models (HMMs) to(More)
—In orthogonal frequency division multiple access (OFDMA) system, the multiple access interference (MAI) is a critical factor that significantly degrades system performance. In this research, a genetic algorithm (GA) is employed for joint channel estimation and multiuser detection. For improving the weakness of GA in exploitation, an approach called(More)
This paper proposes a generalized maximum a posteriori spectral amplitude (GMAPA) algorithm to spectral restoration for speech enhancement. The proposed GMAPA algorithm dynamically adjusts the scale of prior information to calculate the gain function for spectral restoration. In higher signal-to-noise ratio (SNR) conditions, GMAPA adopts a smaller scale to(More)
An indoor activity monitoring system for the elderly is proposed in this paper by using a Fitbit Flex wristband (FFW) and an active RFID. Two methods have been presented for identification of an activity place and a best accuracy of 98.89% has been achieved. The activity level of the elderly is evaluated via dissimilarity measurement by employing an(More)
In distributed speech recognition (DSR), data packets may be lost over error prone channels. A commonly used approach to rectify this is to reconstruct a full frame rate data sequence for recognition using linear interpolation. In this study, an error-concealment decoding method that dynamically adapts the transition probabilities of hidden Markov models to(More)
The hidden Markov models have been widely applied to systems with sequential data. However, the conditional independence of the state outputs will limit the output of a hidden Markov model to be a piecewise constant random sequence, which is not a good approximation for many real processes. In this paper, a high-order hidden Markov model for piecewise(More)