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Melody extraction on midi music files

by Giyasettin Ozcan, Dokuz Eylul, Cihan Isikhan, Dokuz Eylul, Adil Alpkocak, Dokuz Eylul - In Proc. Seventh IEEE International Symposium on Multimedia (ISM’05 , 2005
"... In this study, we propose a new approach to extract monophonic melody from MIDI files and provide a comparison of existing methods. Our approach is based on the elimination of MIDI channels those do not contain melodic information. First, MIDI channels are clustered depending on pitch histogram. Aft ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
In this study, we propose a new approach to extract monophonic melody from MIDI files and provide a comparison of existing methods. Our approach is based on the elimination of MIDI channels those do not contain melodic information. First, MIDI channels are clustered depending on pitch histogram

Query by Humming of MIDI and Audio Using Locality Sensitive Hashing

by Matti Ryynänen, Anssi Klapuri - Proceedings of the 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing. Available online at www.cs.tut.fi/∼mryynane/ryynanen icassp08 , 2008
"... This paper proposes a query by humming method based on locality sensitive hashing (LSH). The method constructs an index of melodic fragments by extracting pitch vectors from a database of melodies. In retrieval, the method automatically transcribes a sung query into notes and then extracts pitch vec ..."
Abstract - Cited by 16 (2 self) - Add to MetaCart
and returned to the user. In our experiments, the method achieved mean reciprocal rank of 0.885 for 2797 queries when searching from a database of 6030 MIDI melodies. To retrieve audio signals, we apply an automatic melody transcription method to construct the melody database directly from music recordings

A pattern recognition approach for melody track selection in midi files. ISMIR

by David Rizo, Pedro J. Ponce De León, Carlos Pérez-sancho, Antonio Pertusa, José M. Iñesta , 2006
"... Standard MIDI files contain data that can be considered as a symbolic representation of music (a digital score), and most of them are structured as a number of tracks. One of them usually contains the melodic line of the piece, while the other tracks contain accompaniment music. The goal of this wor ..."
Abstract - Cited by 17 (5 self) - Add to MetaCart
of this work is to identify the track that contains the melody using statistical properties of the musical content and pattern recognition techniques. Finding that track is very useful for a number of applications, like speeding up melody matching when searching in MIDI databases or motif extraction, among

Manipulation of Music For Melody Matching

by Alexandra L. Uitdenbogerd, Justin Zobel , 1998
"... Large volumes of music are available online, represented in performance formats such as MIDI and, increasingly, in abstract notation such as SMDL. Many types of user would find it valuable to search collections of music via queries representing music fragments, but such searching requires a reliable ..."
Abstract - Cited by 71 (3 self) - Add to MetaCart
Large volumes of music are available online, represented in performance formats such as MIDI and, increasingly, in abstract notation such as SMDL. Many types of user would find it valuable to search collections of music via queries representing music fragments, but such searching requires a

Making Searchable Melodies: Human vs. Machine

by Mark Cartwright, Zafar Rafii, Jinyu Han, Bryan Pardo
"... Systems that find music recordings based on hummed or sung, melodic input are called Query-By-Humming (QBH) systems. Such systems employ search keys that are more similar to a cappella singing than the original recordings. Successful deployed systems use human computation to create these search keys ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
keys: hand-entered MIDI melodies or recordings of a cappella singing. Tunebot is one such system. In this paper, we compare search results using keys built from two automated melody extraction system to those gathered using two populations of humans: local paid singers and Amazon Turk workers.

Making Searchable Melodies: Human versus Machine

by Mark Cartwright, Zafar Rafii, Jinyu Han, Bryan Pardo
"... Systems that find music recordings based on hummed or sung, melodic input are called Query-By-Humming (QBH) systems. Such systems employ search keys that are more similar to a cappella singing than the original recordings. Successful deployed systems use human computation to create these search keys ..."
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keys: hand-entered MIDI melodies or recordings of a cappella singing. Tunebot is one such system. In this paper, we compare search results using keys built from two automated melody extraction system to those gathered using two populations of humans: local paid singers and Amazon Turk workers.

A Complexity-based Approach to Melody Track Identification in MIDI Files ⋆

by Søren Tjagvad Madsen, Gerhard Widmer
"... Abstract. In this paper, we will examine the importance of music complexity as a factor for melody recognition in multi-voiced popular music. The assumption is that the melody (or lead instrument) will contain the largest amount of information – that it will be the least redundant voice. Measures of ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
of melodic complexity calculated from pitch and timing information are proposed. We test the different complexity measures and different prediction strategies, and evaluate them on the task of predicting which track of a MIDI file contains the main melody. Filtering out melody tracks can be useful when

Melody Matching Directly from Audio

by Dominic Mazzoni - Indiana University , 2001
"... In this paper we explore a technique for content-based music retrieval using a continuous pitch contour derived from a recording of the audio query instead of a quantization of the query into discrete notes. Our system determines the pitch for each unit of time in the query and then uses a time-warp ..."
Abstract - Cited by 50 (9 self) - Add to MetaCart
-warping algorithm to match this string of pitches against songs in a database of MIDI files. This technique, while much slower at matching, is usually far more accurate than techniques based on discrete notes. It would be an ideal technique to use to provide the final ranking of candidate results produced by a

Melody Transcription for Interactive Applications

by Rodger J. Mcnab, Lloyd A. Smith - Department of Computer Science University of Waikato , 1996
"... A melody transcription system has been developed to support interactive music applications. The system accepts monophonic voice input ranging from F2 (87 Hz) to G5 (784 Hz) and tracks the frequency, displaying the result in common music notation. Notes are segmented using adaptive thresholds operati ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
A melody transcription system has been developed to support interactive music applications. The system accepts monophonic voice input ranging from F2 (87 Hz) to G5 (784 Hz) and tracks the frequency, displaying the result in common music notation. Notes are segmented using adaptive thresholds

J.M.: Melodic track identification in MIDI files

by David Rizo, Pedro J. Ponce De León, Antonio Pertusa, Josém. Iñesta - In: Proceedings of the 19th International FLAIRS Conference , 2006
"... The objective of this work is to find the melodic line in MIDI files. Usually, the melodic line is stored in a single track, while the other tracks contain the accompaniment. The detection of the track that contains the melodic line can be very useful for a number of applications, such as melody mat ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
The objective of this work is to find the melodic line in MIDI files. Usually, the melodic line is stored in a single track, while the other tracks contain the accompaniment. The detection of the track that contains the melodic line can be very useful for a number of applications, such as melody
Results 1 - 10 of 97