Faculty of Computing

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Author: search.filters.author.Umar Adam IbrahimHas files: Yes

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    Graphic User Interface for Hausa Text-to-Speech System
    (IEEE, 2022-02-02) Umar Adam Ibrahim; Moussa Mahamat Boukar; Muhammed Aliyu Suleiman
    Natural language processing and Digital signal processing are broadly used methods used to enable systems to understand commands and manipulate speech or text. Most of the Text-to-speech done was for major languages such as English, French and others, with no or little for African languages like Hausa, which are termed under resource languages. In this paper, we developed a graphical user interface for the Hausa Text-to-Speech system. This system converts Hausa text to Hausa audio sound, by processing and analyzing it using natural language processing and Digital Signal Processing. Our graphical user interface, aid in converting entered Hausa language text into Hausa speech.
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    Development of Hausa Acoustic Model for Speech Recognition
    ((IJACSA) International Journal of Advanced Computer Science and Applications, 2022-01-02) Umar Adam Ibrahim; Moussa Mahamat Boukar; Muhammad Aliyu Suleiman
    Acoustic modeling is essential for enhancing the accuracy of voice recognition software. To build an automatic speech system and application for any language, building an acoustic model is essential. In this regard, this research is concerned with the development of the Hausa acoustic model for automatic speech recognition. The goal of this work is to design and develop an acoustic model for the Hausa language. This is done by creating a word-level phonemes dataset from the Hausa speech corpus database. Then implement a deep learning algorithm for acoustic modeling. The model was built using Convolutional Neural Network that achieved 83% accuracy. The developed model can be used as a foundation for the development and testing of the Hausa speech recognition system.
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    Development of Hausa dataset a baseline for speech recognition
    (Data in Brief, 2022-01-10) Umar Adam Ibrahim; Moussa Mahamat Boukar; Muhammed Aliyu Suleiman
    The Hausa language read-speech dataset was created by recording native Hausa speakers. The recording took place at Nile university of Nigeria audio studio and radio broadcasting studio. The recorded dataset was segmented into unigram and bigram. The Hausa speech dataset contain 47hr of recorded audio speech. The dataset can be used for automatic speech recognition, speech synthesis, Text-to-Speech and speech-to-text application