Search Results - (( vowel classification using algorithm ) OR ( java application optimisation algorithm ))

Multinomial logistic regression probability ratio-based feature vectors for Malay vowel recognition by Atanda, Abdulwahab Funsho

“…Vowel recognition rates of FELT and 39-MFCC FVs were compared using four different classification techniques of Artificial Neural Network, MLR, Linear Discriminant Analysis, and k-Nearest Neighbour. …”
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Voiceless Bangla vowel recognition using sEMG signal by Sheikh Shanawaz, Mostafa, Mohiuddin, Ahmad, Mohd Abdur, Rashid

“…After that, these prominent features subset is applied in the Artificial Neural Network for vowel classification. This novel Bangla vowel classification method can offer a significant contribution in voice synthesis as well as in speech communication. …”
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Development of Malay word pronunciation application using vowel recognition by Mohd Yusof, Shahrul Azmi

“…In Malaysia, many researchers focus on developing speaker independent systems for training or articulation therapy or to assist language learners to learn about Malay Language or Bahasa Malaysia.Accuracy, noise robustness and processing time are concerns when developing speech therapy systems.In this study, a Malay word pronunciation test application was developed using the first 3 format and fundamental frequencies in an effort to improve pronunciation in Malay.This application was developed using Matlab and uses a vowel recognition algorithm classified using MLP classification technique.The application was developed and tested on UUM undergraduate students.For vowel classification, when fundamental frequency was added, 3-format feature vowel classification rate increased by 1.55% for male gender and 1.48% for female. …”
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Rule-based embedded HMMs phoneme classification to improve Qur’anic recitation recognition by Mohammed Ali Alqadasi, Ammar, Sunar, Mohd Shahrizal, Turaev, Sherzod, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Salam, Md Sah, Alashbi, Abdulaziz Ali Saleh, Ahmed Salem, Ali, Ali, Mohammed A. H.

“…This paper introduces a Rule-Based Phoneme Duration Algorithm to improve phoneme classification in Qur’anic recitation. …”
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Study of noise robustness of First Formant Bandwidth (F1BW) method by Mohd Yusof, Shahrul Azmi, Siraj, Fadzilah, Yaacob, S., M.P, Paulraj, Nazri, Ahmad

“…The performance of speech recognition application under adverse noisy condition often becomes the topic of researchers regardless of the language used. Applications that use vowel phonemes require high degree of Standard Malay vowel recognition capability.In Malaysia, researches in vowel recognition is still lacking especially in the usage of Malay vowels, independent speaker systems, recognition robustness and algorithm speed and accuracy. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani by Mirhassani, Seyedmostafa

“…In the next step, based on the cepstral features provided by the filterbanks a hierarchical phoneme classification is performed. Systems using the provided features were evaluated in phoneme recognition/classification task. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Auditory evoked potential in normal hearing and sensorineural hearing loss among Malay and Chinese adults / Ibrahim Amer Ibrahim by Ibrahim Amer , Ibrahim

“…This study presents accurate and novel formulated indices for classifying brain auditory responses and human hearing abilities. A classification algorithm was used to classify the CAEP responses evoked from multiple auditory stimulus for normal hearing subjects and SNHL patients in the case of both ethnicities. …”
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