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Abstract and goal of the genre detection method

Module by: Yiming Wang

Summary: The abstract of our genre detection method and the goal we try to reach.

Abstract and goal of our genre detection method

Abstract of our genre detection method

Categorizing music isimportant to all music fans nowadays. However, few programs currently existing on the market can automatically, efficiently, and accurately detect the genre of a random chosen song. For example, before customers can search for a list of songs within a certain genre on iTunes, the built-in genre detector for the widely-used ipod series, they have to manually input each song’s genre in order to make it happen. Thus by increasing the accuracy and shortening the detection time, we can come up with a really useful and cool project that will ensure higher quality and customer satisfaction.

Goals

The goal of our genre detection project is to develop a algorithm that detects the genre of any song. The specific genres (our testing pool for now) that we are seeking to detect are rap, classical, rock, jazz, and pop.

Methods of Detection

In our project, we have developed two different techniques to complete the detection process. For both, we created a database “comparison” matrix composed of certain information of the previously mentioned genres. Then in the same way we composed another matrix containing information of the input song and compared it with the database to find the most similar genre. The first technique was with the fast Fourier transform and matrix multiplication. We used matrix multiplication and the dot product to find the similarities between our input song and each genre. The second technique involved finding linear predictive coefficients (LPC), which finds the predicted nth value. The LPC detects genre was based on error while the FFT matrix method achieved the same goal by finding the similarity.

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