首页|Studies in the Area of Machine Learning Reported from Kayseri University (Singer identification model using data augmentation and enhanced feature conversion wi th hybrid feature vector and machine learning)
Studies in the Area of Machine Learning Reported from Kayseri University (Singer identification model using data augmentation and enhanced feature conversion wi th hybrid feature vector and machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting from Kayseri University by NewsRx journalists, research stated, “Analyzing songs is a problem that is being inves tigated to aid various operations on music access platforms.” The news editors obtained a quote from the research from Kayseri University: “At the beginning of these problems is the identification of the person who sings t he song. In this study, a singer identification application, which consists of T urkish singers and works for the Turkish language, is proposed in order to find a solution to this problem. Mel-spectrogram and octave-based spectral contrast v alues are extracted from the songs, and these values are combined into a hybrid feature vector. Thus, problem-specific situations such as determining the differ ences in the voices of the singers and reducing the effects of the year and albu m differences on the result are discussed. As a result of the tests and systemat ic evaluations, it has been shown that a certain level of success has been achie ved in the determination of the singer who sings the song, and that the song is in a stable structure against the changes in the singing style and song structure. The results were analyzed in a database of 9 singers and 180 songs.”
Kayseri UniversityCyborgsEmerging Te chnologiesMachine Learning
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