Audio Quality Improvement

Query by Singing/Humming (QBSH) is a most natural way for music recognition. A QBSH system can help find songs by matching a part of melody users sing or hum. Many Music Information Retrieval (MIR) techniques have been used to carry out the QBSH goal. In the past, little studies had ever been revealed about how to design and implement a simple QBSH system. In this article, we combine Short-Time-Fourier-Transform, Fourier Transform and Spectrum Analysis techniques at the client end, and Dynamic Time Warping (DTW) and dynamic programming techniques at the server end to implement Music Information Retrieval And Gathering Engine (MIRAGE), which can take input queries issued by users from web-based client-ends toward MIRAGE deployed at the server-end. MIRAGE can identify melody when a user only knows the rhythm of a song without any other information.

Music information retrieval is a field of rapidly growing commercial interest. This paper describes TANSEN, a query-by-humming based music retrieval system under development at IIT, Bombay. Named after the legendary musician (and a tenuous acronym for "TA-Note Song Extractor-Navigator), the system is designed to accept acoustic queries in the form of sung fragments, to search a database of Indian film songs. Algorithms for the extraction of melody from the query signal, and pattern matching for search and retrieval from the database are presented. The user interface is described, and experimental results obtained on a prototype version are reported.

The goal of compression techniques is to reducing the size of data and decreasing the communication cost while transferring data. Fractal based coding technique is widely used to compress images files which provides high compression ratio and good image quality. However, like a compression technique, it is still limited because of the difference of the human perceptions between audio and image files, the long time for searching the best possible domain blocks and many comparisons in the encoding process. For those reasons, Fractal Coding had not broadly studied on audio data. Few years ago, Fractal Coding has been extended to apply on the audio data. In this paper, the application of the Fractal Coding on different types of audio files is investigated. Moreover, the effect of block length on the audio quality and compression performance are highlighted since block length is considered the main factor in the Fractal Coding algorithm. A GTZAN dataset is adopted in the evaluation and t...