Feature Extracting in the Presence of Environmental Noise, using Subband Adaptive Filtering

In this work, a new feature extracting method in noisy environments is proposed. The approach is based on subband decomposition of speech signals followed by adaptive filtering in the noisiest subbbands of speech. The speech decomposition is obtained using low complexity octave filter bank, while adaptive filtering is performed using the normalized least mean square algorithm. The performance of the new feature was evaluated for isolated word speech recognition in the presence of a car noise. The proposed method showed higher recognition accuracy than conventional methods in noisy environments

A New Voice Controlled Noise Cancellation Approach

This paper presents a new approach to control the operation of adaptive noise cancellers (ANCs). The technique is based on using the residual output from the noise canceller to control the decision made by a voice activity detector (VAD). Threshold of full band energy feature is adjusted according to the residual output of the noise canceller. In variable background noise environment, the threshold controlled VAD prohibits the reference input from containing some components of actual speech signal during adaptation periods. The convergence behavior of the adaptive filter is greatly improved, since the reference input will be highly correlated with the primary input. In addition, the computation power will be reduced since the output of the adaptive filter will be calculated only during non- speech periods. The threshold controlled noise canceller achieves a cleaner output in about 50% of the time required by a non-controlled noise canceller

Adaptive cancellation of localised environmental noise

Noise cancellation systems are useful in applications such as speech and speaker recognition systems where the effects of environmental noise have to be taken into considerations. A robust method for the cancellation of localised noise in noisy speech signals using subband decomposition and adaptive filtering is presented and described in this paper. The subband decomposition technique is based on low complexity octave filters that split the noisy speech input into subsidiary bands. A thresholding technique is then applied to the subbands to determine the presence or absence of environmental noise. This is used to control an adaptive filter which only responds to the noisy parts of the speech spectrum hence localising the adaptation process only on these segments. The Normalised Least Mean Squares algorithm (NLMS) is used for the adaptation process. A comparison with a similar system without localising the environmental noise shows the superior performance of the proposed system. It has been shown to perform better in terms of computational costs and convergence rate when compared to a system that does not take advantage of the information regarding the presence or absence of noise in a specific part of the speech spectrum. More than 35 dB of noise has been eliminated in less iterations than in conventional approach which needs longer time to reach steady state

Objective and Subjective Evaluations of Adaptive Noise Cancellation Systems with Selectable Algorithms for Speech Intelligibility

Adaptive Noise Cancellation (ANC) systems with selectable algorithms refer to ANC systems that are able to change the adaptation algorithm based on the eigenvalue spread of the noise. These systems can have dual inputs based on the conventional ANC structure or a single input based on the Adaptive Line Enhancer (ALE) structure. This paper presents a comparison of the performance of these two systems using objective and subjective measurements for speech intelligibility. The parameters used to objectively compare the systems are the Mean Square Error (MSE) and the output Signal to Noise Ratio (SNR). For subjective evaluation, listening tests were evaluated using the Mean Opinion Score (MOS) technique. The outcomes demonstrate that for both objective and subjection evaluations, the single input ALE with selectable algorithms (S-ALE) system outperforms that of the dual input ANC with selectable algorithm (S-ANC) in terms of better steady-state MSE by 10%, higher SNR values for most types of noise, higher scores in most of the questions in the MOS questionnaire and a higher acceptance rate for speech quality

Money Attitude and Socio-Demographic Factors as Determinants of University Students’ Spending Behavior in Shah Alam, Malaysia

ABSTRACTNowadays, uncontrollable spending habit towards Malaysian young generations are becoming progressively. They have a tendency to have less value of money compared to the elder generations in spending their money. Since the cost of living in Malaysia has improved remarkably, the young generations enjoyed spending their money heavenly, therefore Malaysia faced changes in lifestyle and spending trend. This study proposes to investigate the relationship between money attitude and socio-demographic as determinants of college students’ spending behaviours. As such, the correlation between money attitude factors (power-prestige, distrust, retention-time and anxiety) and spending behaviours among Malaysian college students is a topic worthy of further exploration. At the same time, this study also attempts to explore whether college students’ spending behaviours are affected by their socio-demographic factors such as gender, age. The sample of this study consists of 176 students from three different universities in the Shah Alam area i.e University Selangor (UNISEL), University Management Science (MSU) and Universiti Teknologi Malaysia (UiTM). The regression analysis showed that there were only two factors of money attitude (power-prestige, and anxiety) that had a significant effect on spending behaviour among these universities’ students. However, from the analysis, it can be revealed that none of the socio-demographic factors had a significance (more than 0.05) towards the spending behaviour of the students. Thus, age (positive result) is the most influenced factor of the students’ spending behaviour. Consequently, several suggestions have been put forward and hoped that it will assist students in managing their fund effectivel

Perbandingan Konjugasi Kata Kerja Bahasa Jerman, Bahasa Arab dan Bahasa Melayu: Satu Tinjauan di UMP

Makalah ini membincangkan hasil perbandingan bentuk konjugasi kata kerja (KK) antara bahasa Jerman (BJ), bahasa Arab (BA) dengan bahasa Melayu (BM) yang dibina oleh pelajar UMP. Menurut Tatabahasa Dewan(2008) penggunaan KK yang tepat memainkan peranan utama kerana KK berfungsi sebagai predikat iaitu sebagai unsur yang menerangkan atau memperihalkan KN dalam sesuatu ayat. KK mempunyai ciri morfologi atau unsur makna sama ada perbuatan, keadaan atau proses (Kamus Linguistik, 1982). Secara lebih khusus, data dalam kajian ini melibatkan penggunaan konjugasi sistem kala kini atau Präsens BJ dan الفعل المضارع )Fi’il Mudhari’) BA yang diambil daripada jawapan para pelajar yang mengambil kursus BA dan BJ. Berdasarkan tema “Memperkenalkan Diri”, terdapat 10 kata kerja berbentuk Präsens dalam BJ dan الفعل المضارع )Fi’il Mudhari’) dalam BA. Data ini dianalisis secara deskriptif melalui pendekatan kontrastif dengan BM berasaskan Tatabahasa Dewan. Hasilnya menunjukkan bahawa terdapat perbezaan dan kepelbagaian bentuk konjugasi KK yang dibina oleh para pelajar. Dalam hal ini, pengkaji mendapati para pelajar ini sering keliru ketika mengkonjugasikan KK dalam bahasa Asing (BAs) kerana terdapat pengaruh bahasa pertama (B1) dalam struktur konjugasi yang dibina. Hal ini dapat dikaitkan dengan faktor dalaman dan luaran bahasa iaitu pengaruh tatabahasa B1 yang kuat dan juga tahap penguasaan tatabahasa BAs yang masih lemah atau belum memadai

Perbandingan Konjugasi Kata Kerja Bahasa Jerman, Bahasa Arab dan Bahasa Melayu: Satu Tinjauan di UMP

Makalah ini membincangkan hasil perbandingan bentuk konjugasi kata kerja (KK) antara bahasa Jerman (BJ), bahasa Arab (BA) dengan bahasa Melayu (BM) yang dibina oleh pelajar UMP. Menurut Tatabahasa Dewan(2008) penggunaan KK yang tepat memainkan peranan utama kerana KK berfungsi sebagai predikat iaitu sebagai unsur yang menerangkan atau memperihalkan KN dalam sesuatu ayat. KK mempunyai ciri morfologi atau unsur makna sama ada perbuatan, keadaan atau proses (Kamus Linguistik, 1982). Secara lebih khusus, data dalam kajian ini melibatkan penggunaan konjugasi sistem kala kini atau Präsens BJ dan الفعل المضارع )Fi’il Mudhari’) BA yang diambil daripada jawapan para pelajar yang mengambil kursus BA dan BJ. Berdasarkan tema “Memperkenalkan Diri”, terdapat 10 kata kerja berbentuk Präsens dalam BJ dan الفعل المضارع )Fi’il Mudhari’) dalam BA. Data ini dianalisis secara deskriptif melalui pendekatan kontrastif dengan BM berasaskan Tatabahasa Dewan. Hasilnya menunjukkan bahawa terdapat perbezaan dan kepelbagaian bentuk konjugasi KK yang dibina oleh para pelajar. Dalam hal ini, pengkaji mendapati para pelajar ini sering keliru ketika mengkonjugasikan KK dalam bahasa Asing (BAs) kerana terdapat pengaruh bahasa pertama (B1) dalam struktur konjugasi yang dibina. Hal ini dapat dikaitkan dengan faktor dalaman dan luaran bahasa iaitu pengaruh tatabahasa B1 yang kuat dan juga tahap penguasaan tatabahasa BAs yang masih lemah atau belum memadai

An Electronic Nose for Reliable Measurement and Correct Classification of Beverages

This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results