Faculty of Computing
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Publication Embargo Self-speech evaluation with speech recognition and gesture analysis(IEEE, 2018-10-02) Shangavi, S; Jeyamaalmarukan, S; Jathevan, A; Umatharsini, M; Samarasinghe, PSpeaking helps people to improve their communication, public speaking and leadership skills. There are two main techniques that help a speaker to deliver a meaningful speech. The techniques are voice transition which expresses a verbal message and gestures that convey the message to an audience. A famous organization to help and improvise speech is Toastmasters. Their systems of evaluation are such as, Tracking Filler words, Usage of Redundant words and Phrases, Checking Grammar and Pronunciation, Usage of Body Movements and Gestures, Tracking Vocal Variations and Time Management. If an ordinary person wants to self-evaluate his or her speech, that person has to be a member of a Toastmasters Club or any other speech improvising organization. By using our application, it is possible for a person to evaluate his or her own speech without depending on an organization. All the above-mentioned criteria in manual evaluation processes are included in this application. Since nowadays mobile applications are frequent in use, our system is proposed in Android Platform. Several techniques and methods are used to interconnect with Android such as OpenCV, Microsoft Cognitive Services and MATLAB in order to achieve the objectives of the application. Acoustic Model, Support Vector Model (SVM), Hidden Markov Model (HMM) are some models used to build the application more efficient by giving approximately accurate results.Publication Embargo E-Learning Platform for Hearing Impaired Students(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Krishnamoorthy, N.; Raveendran, A.; Vadiveswaran, P.; Arulraj, S.R.; Manathunga, K.; Siriwardana, S.With the Spread of global pandemic Covid-19, the traditional education was transformed to online from traditional learning drastically. Hence the use of e-Learning platforms was increased. But this idea has issues with certain communities of people around the world. The hearing-impaired people have many issues with eLearning platforms because of their deficiency in hearing sound. Therefore, through this paper authors are introducing a learning platform for hearing impaired communities to aid in learning effectively. The proposed platform uses sign language to facilitate communication among students and tutors while providing sign language learning materials, practicing opportunities and Q&A sessions. The system has a low light enhancement module to enhance the videos uploaded by the tutor, module to convert the uploaded videos to American Sign Language and it also converts the questions asked via sign language to text.Publication Embargo Digital Preservation and Noise Reduction using Machine Learning(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Aravinda, K.P.; Sandeepa, K.G.H.; Sedara, V. V.; Chamodya, A.K.Y.L.; Dharmasena, T.; Abeygunawardhana, P.K.W.This paper proposes a digital preservation solution for Sinhala audios to conserve those as documents with noise reduction. The solution has implemented multiple noise reduction techniques as a pre-processing step to remove unwanted internal and external noises. A two-step, two-way noise reduction process is applied to produce clean audios based on Deep Convolutional Neural Network (DCNN) and adaptive filter-based techniques. This approach implements two separate noise reduction models for internal and external noises. After that, the speech recognition decoder recognizes the speech and converts it to a Unicode document by acoustic, language, and pronunciation models using extracted audio features from the denoised audio. Further, noise reduction models are decoupled from the preservation solution and exposed as a sub solution for multilingualism noise reduction, supporting English and Sinhala audios.Publication Embargo Digital Preservation and Noise Reduction using Machine Learning(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Aravinda, K.P.; Sandeepa, K.G.H.; Sedara, V. V.; Chamodya, A.K.Y.L.; Dharmasena, T.; Abeygunawardhana, P.K.W.This paper proposes a digital preservation solution for Sinhala audios to conserve those as documents with noise reduction. The solution has implemented multiple noise reduction techniques as a pre-processing step to remove unwanted internal and external noises. A two-step, two-way noise reduction process is applied to produce clean audios based on Deep Convolutional Neural Network (DCNN) and adaptive filter-based techniques. This approach implements two separate noise reduction models for internal and external noises. After that, the speech recognition decoder recognizes the speech and converts it to a Unicode document by acoustic, language, and pronunciation models using extracted audio features from the denoised audio. Further, noise reduction models are decoupled from the preservation solution and exposed as a sub solution for multilingualism noise reduction, supporting English and Sinhala audios.