Abstract: Emotion in speech is an issue that has been attracting
the interest of the speech community for many years, both in the
context of speech synthesis as well as in automatic speech
recognition (ASR). In spite of the remarkable recent progress in
Large Vocabulary Recognition (LVR), it is still far behind the
ultimate goal of recognising free conversational speech uttered by
any speaker in any environment. Current experimental tests prove
that using state of the art large vocabulary recognition systems the
error rate increases substantially when applied to
spontaneous/emotional speech. This paper shows that recognition
rate for emotionally coloured speech can be improved by using a
language model based on increased representation of emotional
utterances.
Abstract: Analytically the effect of polarization dependent loss on a high speed fiber optic communication link has been investigated. PDL and the signal's incoming state of polarization (SOP) have a significant co-relation between them and their various combinations produces different effects on the system behavior which has been inspected. Pauli's spin operator and PDL parameters are combined together to observe the attenuation effect induced by PDL in a link containing multiple PDL elements. It is found that in the presence of PDL the Q-factor and BER at the receiver undergoes fluctuation causing the system to be unstable and results show that it is mainly due to optical-signal-to-parallel-noise ratio (OSNItpar) that these parameters fluctuate. Generally the Q-factor, BER deteriorates as the value of average PDL in the link increases except for depolarized light for which the system parameters improves when PDL increases.
Abstract: A generalized Digital Modulation Identification algorithm for adaptive demodulator has been developed and presented in this paper. The algorithm developed is verified using wavelet Transform and histogram computation to identify QPSK and QAM with GMSK and M–ary FSK modulations. It has been found that the histogram peaks simplifies the procedure for identification. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB and 12 dB for GMSK and QPSK respectively. When SNR is above 5 dB the throughput of the proposed algorithm is more than 97.8%. The receiver operating characteristics (ROC) has been computed to measure the performance of the proposed algorithm and the analysis shows that the probability of detection (Pd) drops rapidly when SNR is 5 dB and probability of false alarm (Pf) is smaller than 0.3. The performance of the proposed algorithm has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.
Abstract: In this paper, a new robust audio fingerprinting
algorithm in MP3 compressed domain is proposed with high
robustness to time scale modification (TSM). Instead of simply
employing short-term information of the MP3 stream, the new
algorithm extracts the long-term features in MP3 compressed domain
by using the modulation frequency analysis. Our experiment has
demonstrated that the proposed method can achieve a hit rate of
above 95% in audio retrieval and resist the attack of 20% TSM. It has
lower bit error rate (BER) performance compared to the other
algorithms. The proposed algorithm can also be used in other
compressed domains, such as AAC.
Abstract: This interdisciplinary study is an investigation to evaluate user-interfaces in business administration. The study is going to be implemented on two computerized business administration systems with two distinctive user-interfaces, so that differences between the two systems can be determined. Both systems, a commercial and a prototype developed for the purpose of this study, deal with ordering of supplies, tendering procedures, issuing purchase orders, controlling the movement of the stocks against their actual balances on the shelves and editing them on their tabulations. In the second suggested system, modern computer graphics and multimedia issues were taken into consideration to cover the drawbacks of the first system. To highlight differences between the two investigated systems regarding some chosen standard quality criteria, the study employs various statistical techniques and methods to evaluate the users- interaction with both systems. The study variables are divided into two divisions: independent representing the interfaces of the two systems, and dependent embracing efficiency, effectiveness, satisfaction, error rate etc.
Abstract: The paper presents a multimodal approach for biometric authentication, based on multiple classifiers. The proposed solution uses a post-classification biometric fusion method in which the biometric data classifiers outputs are combined in order to improve the overall biometric system performance by decreasing the classification error rates. The paper shows also the biometric recognition task improvement by means of a carefully feature selection, as much as not all of the feature vectors components support the accuracy improvement.
Abstract: This paper addresses the problem of peak-to-average
power ratio (PAPR) in orthogonal frequency division multiplexing
(OFDM) systems. It also introduces a new PAPR reduction technique
based on adaptive square-rooting (SQRT) companding process. The
SQRT process of the proposed technique changes the statistical
characteristics of the OFDM output signals from Rayleigh
distribution to Gaussian-like distribution. This change in statistical
distribution results changes of both the peak and average power
values of OFDM signals, and consequently reduces significantly the
PAPR. For the 64QAM OFDM system using 512 subcarriers, up to 6
dB reduction in PAPR was achieved by square-rooting technique
with fixed degradation in bit error rate (BER) equal to 3 dB.
However, the PAPR is reduced at the expense of only -15 dB out-ofband
spectral shoulder re-growth below the in-band signal level. The
proposed adaptive SQRT technique is superior in terms of BER
performance than the original, non-adaptive, square-rooting
technique when the required reduction in PAPR is no more than 5
dB. Also, it provides fixed amount of PAPR reduction in which it is
not available in the original SQRT technique.
Abstract: The study in this paper underlines the importance of
correct joint selection of the spreading codes for uplink of multicarrier
code division multiple access (MC-CDMA) at the transmitter
side and detector at the receiver side in the presence of nonlinear
distortion due to high power amplifier (HPA). The bit error rate
(BER) of system for different spreading sequences (Walsh code, Gold
code, orthogonal Gold code, Golay code and Zadoff-Chu code) and
different kinds of receivers (minimum mean-square error receiver
(MMSE-MUD) and microstatistic multi-user receiver (MSF-MUD))
is compared by means of simulations for MC-CDMA transmission
system. Finally, the results of analysis will show, that the application
of MSF-MUD in combination with Golay codes can outperform
significantly the other tested spreading codes and receivers for all
mostly used models of HPA.
Abstract: By employing BS (Base Station) cooperation we can
increase substantially the spectral efficiency and capacity of cellular
systems. The signals received at each BS are sent to a central unit that
performs the separation of the different MT (Mobile Terminal) using
the same physical channel. However, we need accurate sampling and
quantization of those signals so as to reduce the backhaul
communication requirements.
In this paper we consider the optimization of the quantizers for BS
cooperation systems. Four different quantizer types are analyzed and
optimized to allow better SQNR (Signal-to-Quantization Noise
Ratio) and BER (Bit Error Rate) performance.
Abstract: In this paper we present an efficient system for
independent speaker speech recognition based on neural network
approach. The proposed architecture comprises two phases: a
preprocessing phase which consists in segmental normalization and
features extraction and a classification phase which uses neural
networks based on nonparametric density estimation namely the
general regression neural network (GRNN). The relative
performances of the proposed model are compared to the similar
recognition systems based on the Multilayer Perceptron (MLP), the
Recurrent Neural Network (RNN) and the well known Discrete
Hidden Markov Model (HMM-VQ) that we have achieved also.
Experimental results obtained with Arabic digits have shown that the
use of nonparametric density estimation with an appropriate
smoothing factor (spread) improves the generalization power of the
neural network. The word error rate (WER) is reduced significantly
over the baseline HMM method. GRNN computation is a successful
alternative to the other neural network and DHMM.