Effectiveness of note duration information for music retrieval

Content-based music information retrieval uses features extracted from music to answer queries. For melodic queries, the two main features are the pitch and duration of notes. The note pitch feature has been well researched whereas duration has not been fully explored. In this paper, we discuss how the note duration feature can be used to alter music retrieval effectiveness. Notes are represented by strings called standardisations. A standardisation is designed for approximate string matching and may not capture melodic information precisely. To represent pitches, we use a string of pitch differences. Our duration standardisation uses a string of five symbols representing the relative durations of adjacent notes. For both features, the Smith-Waterman alignment is used for matching. We demonstrate combining the similarity in both features using a vector model. Results of our experiments in retrieval effectiveness show that note duration similarity by itself is not useful for effective music retrieval. Combining pitch and duration similarity using the vector model does not improve retrieval effectiveness over the use of pitch on its own

Music ranking techniques evaluated

In a music retrieval system, a user presents a piece of music as a query and the system must identify from a corpus of performances other pieces with a similar melody. Several techniques have been proposed for matching such queries to stored music. In previous work, we found that local alignment, a technique derived from bioinformatics, was more effective than the n-gram methods derived from information retrieval; other researchers have reported success with n-grams, but have not compared against local alignment. In this paper we explore a broader range of n-gram techniques, and test them with both manual queries and queries automatically extracted from MIDI files. Our experiments show that n-gram matching techniques can be as effective as local alignment; one highly effective technique is to simply count the number of n-grams in common between the query and the stored piece of music. N-grams are particularly effective for short queries and manual queries, while local alignment is superior for automatic queries

The effect of using pitch and duration for symbolic music retrieval

Quite reasonable retrieval effectiveness is achieved for retrieving polyphonic (multiple notes at once) music that is symbolically encoded via melody queries, using relatively simple pattern matching techniques based on pitch sequences. Earlier work showed that adding duration information was not particularly helpful for improving retrieval effectiveness. In this paper we demonstrate that defining the duration information as the time interval between consecutive notes does lead to more effective retrieval when combined with pitch-based pattern matching in our collection of over 14 000 MIDI files

Exploring microtonal matching

Most research intomusic information retrieval thus far has only examined music from the western tradition. However, music of other origins often conforms to different tuning systems. Therefore there are problems both in representing this music as well as finding matches to queries from these diverse tuning systems. We discuss the issues associated with microtonal music retrieval and present some preliminary results from an experiment in applying scoring matrices to microtonal matching

Using contour as a mid-level representation of melody

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1996.Includes bibliographical references (p. 75-76).by Adam Taro Lindsay.M.S

Content-based Retrieval of Music Using Monophonic Queries on a Database of Polyphonic, Midi Information

Due to the large amount of musical data available on the internet in recent years, efficient and intuitive methods are required for searching the musical data. Musical search services, such as the iTunes provides, support querying capabilities on the basis of metadata tags (title, artist, etc) associated with the musical data. The natural way of searching musical data is to search by its content rather than secondary features like title, genre etc, because the content is usually more memorable. In this research, content-based music retrieval is performed on a polyphonic MIDI music database where the query is a hummed tune. Two approximate string matching algorithms, LCTS and Myers algorithms are modified, applied to the problem, and retrieval performance is calculated. Response times of the algorithms are calculated by altering the values of some of the interesting parameters such as the query length, degree of polyphony and size of the database.Computer Science Departmen

Content-based music retrieval by acoustic query

Ph.DDOCTOR OF PHILOSOPH