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Govind Ballabh Pant University of Agriculture and Technology, Pantnagar

After independence, development of the rural sector was considered the primary concern of the Government of India. In 1949, with the appointment of the Radhakrishnan University Education Commission, imparting of agricultural education through the setting up of rural universities became the focal point. Later, in 1954 an Indo-American team led by Dr. K.R. Damle, the Vice-President of ICAR, was constituted that arrived at the idea of establishing a Rural University on the land-grant pattern of USA. As a consequence a contract between the Government of India, the Technical Cooperation Mission and some land-grant universities of USA, was signed to promote agricultural education in the country. The US universities included the universities of Tennessee, the Ohio State University, the Kansas State University, The University of Illinois, the Pennsylvania State University and the University of Missouri. The task of assisting Uttar Pradesh in establishing an agricultural university was assigned to the University of Illinois which signed a contract in 1959 to establish an agricultural University in the State. Dean, H.W. Hannah, of the University of Illinois prepared a blueprint for a Rural University to be set up at the Tarai State Farm in the district Nainital, UP. In the initial stage the University of Illinois also offered the services of its scientists and teachers. Thus, in 1960, the first agricultural university of India, UP Agricultural University, came into being by an Act of legislation, UP Act XI-V of 1958. The Act was later amended under UP Universities Re-enactment and Amendment Act 1972 and the University was rechristened as Govind Ballabh Pant University of Agriculture and Technology keeping in view the contributions of Pt. Govind Ballabh Pant, the then Chief Minister of UP. The University was dedicated to the Nation by the first Prime Minister of India Pt Jawaharlal Nehru on 17 November 1960. The G.B. Pant University is a symbol of successful partnership between India and the United States. The establishment of this university brought about a revolution in agricultural education, research and extension. It paved the way for setting up of 31 other agricultural universities in the country.

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  • ThesisItemOpen Access
    Music genre classification using convolutional neural network
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-02) Bhandari, Neema; Singh, B.K.
    Music applications are one of the most used applications in the world. Music Genre Classification (MGC) has been gaining attention with the rise of digital music and it is a useful tool for semantic information to music tracks in offline and online music collections. A music genre refers to a specific class of music with a set of common properties. A mere perception of the music of that class can help one to distinguish it from other classes. Musical genre classification is a promising yet difficult task in the field of musical information retrieval. To determine the genre of a song it has to be distinguished by its unique audio features so that its contents can be analyzed with respect to the produced wave signals. A single Music Genre is a set of different features that combined with a specific pattern of rhythm, melody, harmony, instruments, mood and attitude, lyrics and language. In the Western music there has been much work done in the area of automatic tagging genre recognition, classification and comparative studies as compare to the Indian music. As a widely used feature in genre classification systems, Mel-frequency cepstral coefficients (MFCC) is typically believed to encode timbral information, since it represents shortduration musical textures. In this thesis, we investigate the invariance of MFCC and show that MFCCs in fact encode both timbral and key information. Convolutional Neural Networks have additional layers for edge detection that make them well suited for classification problems. For the convolutional base classification, we used a common pattern one is a stack of Conv2D and second one is MaxPooling2D layers. In this research work we use six semi classical Indian music genre like Abhang, Bhajan, Kajari, Qawwali, Tappa and Thumri.