Giuliano Monti

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This paper extends the familiar “query by humming” music retrieval framework into the polyphonic realm. As humming in multiple voices is quite difficult, the task is more accurately described as “query by audio example”, onto a collection of scores. To our knowledge, we are the first to use polyphonic audio queries to retrieve from polyphonic symbolic(More)
Two systems are reviewed than perform automatic music transcription. The first perform monophonic transcription using an autocorrelation pitch tracker. The algorithm takes advantage of some heuristic parameters related to the similarity between image and sound in the collector. The detection is correct between notes B1 to E6 and further timbre analysis will(More)
2 In this article, we give an overview of a range of approaches to the analysis and separation of musical audio. In particular, we consider the problems of automatic music transcription and audio source separation, which are of particular interest to our group. Monophonic music transcription, where a single note is present at one time, can be tackled using(More)
This paper describes an algorithm, which performs monophonic music transcription. A pitch tracker calculates the fundamental frequency of the signal from the autocorrelation function. A continuity-restoration block takes the extracted pitch and determines the score corresponding to the original performance. The signal envelope analysis completes the(More)
This paper extends the familiar “query by humming” music retrieval framework into the polyphonic realm. As humming in multiple voices is quite difficult, the task is more accurately described as “query by audio example”, onto a collection of scores. To our knowledge, we are the first to use polyphonic audio queries to retrieve from polyphonic symbolic(More)
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