{"id":{"repo_id":"nus","oai_identifier":"oai:scholarbank.nus.edu.sg:10635/14188"},"canonical_url":"https://search.dev.ndltd.org/etd/nus/oai:scholarbank.nus.edu.sg:10635/14188","repository":{"repo_id":"nus","name":"National University of Singapore","base_url":"https://scholarbank.nus.edu.sg/oai/request"},"display":{"title":"Music transcription using instrument model","abstract":"Music transcription can be defined as the act of listening to a piece of music and writing down the music notation for the notes that constitute the piece, either manually by humans or automatically by machines. Automated music transcription has many applications and is indispensable in music retrieval and remixing.One of the most important and difficult parts in music transcription is pitch estimation. Since the transcription of monophonic music is considered a solved problem, our research focuses on the transcription of polyphonic music.We introduce a method to transcribe music with the help of an instrument model. The instrument model provides the harmonic structure of instruments, which is very helpful to polyphonic pitch estimation in the situations such as missing fundamental, missing harmonics and sharing frequencies. The model can be easily built up with instrument samples. We devise a spectrum subtraction algorithm and implement a system to transcribe polyphonic single-instrument music. The algorithm can be extended to transcribe polyphonic multi-instrument music as well. Through experiments, we find our method outperforms many current methods.","abstract_html":"Music transcription can be defined as the act of listening to a piece of music and writing down the music notation for the notes that constitute the piece, either manually by humans or automatically by machines. Automated music transcription has many applications and is indispensable in music retrieval and remixing.One of the most important and difficult parts in music transcription is pitch estimation. Since the transcription of monophonic music is considered a solved problem, our research focuses on the transcription of polyphonic music.We introduce a method to transcribe music with the help of an instrument model. The instrument model provides the harmonic structure of instruments, which is very helpful to polyphonic pitch estimation in the situations such as missing fundamental, missing harmonics and sharing frequencies. The model can be easily built up with instrument samples. We devise a spectrum subtraction algorithm and implement a system to transcribe polyphonic single-instrument music. The algorithm can be extended to transcribe polyphonic multi-instrument music as well. Through experiments, we find our method outperforms many current methods.","abstract_has_math":false,"creators":["YIN JUN"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004-07-22","date_published":"2004-07-22","updated_at":"2026-07-24T03:31:38Z","subjects":["music transcription, pitch estimation, harmonic structure, instrument model, note"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["YIN JUN"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2004-07-22"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://scholarbank.nus.edu.sg/handle/10635/14188"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["music transcription, pitch estimation, harmonic structure, instrument model, note"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://scholarbank.nus.edu.sg/bitstreams/3067255d-8721-4c76-9967-b09f804e3aee/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Music transcription can be defined as the act of listening to a piece of music and writing down the music notation for the notes that constitute the piece, either manually by humans or automatically by machines. Automated music transcription has many applications and is indispensable in music retrieval and remixing.One of the most important and difficult parts in music transcription is pitch estimation. Since the transcription of monophonic music is considered a solved problem, our research focuses on the transcription of polyphonic music.We introduce a method to transcribe music with the help of an instrument model. The instrument model provides the harmonic structure of instruments, which is very helpful to polyphonic pitch estimation in the situations such as missing fundamental, missing harmonics and sharing frequencies. The model can be easily built up with instrument samples. We devise a spectrum subtraction algorithm and implement a system to transcribe polyphonic single-instrument music. The algorithm can be extended to transcribe polyphonic multi-instrument music as well. 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Since the transcription of monophonic music is considered a solved problem, our research focuses on the transcription of polyphonic music.We introduce a method to transcribe music with the help of an instrument model. The instrument model provides the harmonic structure of instruments, which is very helpful to polyphonic pitch estimation in the situations such as missing fundamental, missing harmonics and sharing frequencies. The model can be easily built up with instrument samples. We devise a spectrum subtraction algorithm and implement a system to transcribe polyphonic single-instrument music. The algorithm can be extended to transcribe polyphonic multi-instrument music as well. 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