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    Deep Learning for Speech Recognition

    , M.Sc. Thesis Sharif University of Technology Azadi Yazdi, Saman (Author) ; Sameti, Hossein (Supervisor)
    Abstract
    Speech recognition is one of the first goals of speech processing. Our goal in this thesis is to use deep learning for speech recognition. In recent years little improvement of speech recognition accuracies are reported. Deep learning is a new learning algorithm that results in improvement in many machine learning tasks. Following improvements reported in speech recognition in English language by deep learning, in this thesis we tried to improve accuracy over common and new recognition methods for Persian language.
    First the overall structure of a typical speech recognition system is introduced. For this purpose, the modules of a speech recognition system are introduced. Deep multilayer... 

    Speech Activity Detection Using Deep Networks

    , M.Sc. Thesis Sharif University of Technology Shahsavari, Sajad (Author) ; Sameti, Hossein (Supervisor)
    Abstract
    In this paper, we introduce a new dataset for SAD and evaluate certain common methods such as GMM, ANN, and RNN on it. We have collected our dataset in a semi-supervised approach, using subtitled movies, with a labeling accuracy of 95%. This semi-automatic method can help us collect huge amounts of labeled audio data with very high diversity in language, speaker, and channel. We model the problem of SAD as a classification task to two classes of speech and non-speech. When using GMM for this problem, we use two separate mixtures to model speech and non-speech. In the case of neural networks, we use a softmax layer at the end of the network, with two neurons which represent speech and... 

    Performance Evaluation and Improvement of Duplicate Question Detection in Developers’ Online Q&A Community

    , M.Sc. Thesis Sharif University of Technology Daliri, Majid (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    In this research, we study one of the challenges in the field of software engineering, namely the detection of diplicate questions in Stackoverflow, the Q&A community of programmers. The works done in this area has problems such as complexity and reduced performance over time. The proposed solution is based on machine learning and modern representation learning methods. Representation is done with two approaches, domain specific learning and transfer learning. Fasttext and GloVe, the two word embeddings used in domain specific learning, and in transfer learning, the embedding of the universal sentence encoder has been used. Support vector machine and multilayer perceptron used as...