{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/36769"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/36769","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"The Music Muse","abstract":"Ever wonder why two people can sing the same note with the same loudness, but sound completely different? Middle C is middle C no matter who sings it, yet for some reason Lucianno Pavarotti1s middle C sounds richer and more beautiful than Bob Dylan1s middle C, for example. But then again, what is beauty in singing? It is a completely biased and abstract concept. To some, Bob Dylan1s voice may epitomize tonal beauty, while to others his voice may be comparable to fingernails on a chalk board. Anyway, differences in tone quality, or timbre, are due to differences in the spectral characteristics in different voices. The Music Muse is a computer program designed to help singers train their voices by showing them the individual components of their voices that combine to produce timbre. In paintings, many colors are combined to produce different hues and shades of color. The individual colors that make up the hue are difficult to distinguish. Similarly in music, harmonics with varying amplitudes combine to create voice colors, or timbres. These individual harmonics are difficult to distinguish by the ear alone. The Music Muse splits the voice up into its harmonic components by means of a Fourier transform. The transformed data is then plotted on a harmonic spectrum, from which singers can observe the number of harmonics in their tone, and their amplitudes relative to one another. It is these spectral characteristics that are important to voice timbre. The amplitudes of the harmonics in a voiced tone are determined by the resonant frequencies of the vocal tract. These resonances are called formants. When a harmonic that is produced by the vocal cords has a frequency that is at or near a formant frequency, it is amplified. Formants are determined by the length, size, and shape of the vocal tract. These parameters differ from person to person, and change during articulation. Optimal tonal quality during singing is obtained by placing formants at a desired frequency. The Music Muse calculates the formants of the voice by means of cepstral analysis. The formants are then plotted. With this tool, singers can learn how to place their formants. One of the difficulties of voice training is that singing is rated on a scale of quality, which is difficult to quantify. Also, feedback tends to be biased, and therefore subjective in nature. The Music Muse provides singers with the technology to quantify quality to a degree that makes it less of an abstract concept, and therefore more attainable.","abstract_html":"Ever wonder why two people can sing the same note with the same loudness, but sound completely different? Middle C is middle C no matter who sings it, yet for some reason Lucianno Pavarotti1s middle C sounds richer and more beautiful than Bob Dylan1s middle C, for example. But then again, what is beauty in singing? It is a completely biased and abstract concept. To some, Bob Dylan1s voice may epitomize tonal beauty, while to others his voice may be comparable to fingernails on a chalk board. Anyway, differences in tone quality, or timbre, are due to differences in the spectral characteristics in different voices. The Music Muse is a computer program designed to help singers train their voices by showing them the individual components of their voices that combine to produce timbre. In paintings, many colors are combined to produce different hues and shades of color. The individual colors that make up the hue are difficult to distinguish. Similarly in music, harmonics with varying amplitudes combine to create voice colors, or timbres. These individual harmonics are difficult to distinguish by the ear alone. The Music Muse splits the voice up into its harmonic components by means of a Fourier transform. The transformed data is then plotted on a harmonic spectrum, from which singers can observe the number of harmonics in their tone, and their amplitudes relative to one another. It is these spectral characteristics that are important to voice timbre. The amplitudes of the harmonics in a voiced tone are determined by the resonant frequencies of the vocal tract. These resonances are called formants. When a harmonic that is produced by the vocal cords has a frequency that is at or near a formant frequency, it is amplified. Formants are determined by the length, size, and shape of the vocal tract. These parameters differ from person to person, and change during articulation. Optimal tonal quality during singing is obtained by placing formants at a desired frequency. The Music Muse calculates the formants of the voice by means of cepstral analysis. The formants are then plotted. With this tool, singers can learn how to place their formants. One of the difficulties of voice training is that singing is rated on a scale of quality, which is difficult to quantify. Also, feedback tends to be biased, and therefore subjective in nature. The Music Muse provides singers with the technology to quantify quality to a degree that makes it less of an abstract concept, and therefore more attainable.","abstract_has_math":false,"creators":["Wilson, Leslie"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Wicks, Alfred L."],"committee_members":["Saunders, William R.","Burdisso, Ricardo A."],"year":1996,"date_issued":"1996-11-01","date_published":"1996-11-01","updated_at":"2026-07-22T22:19:37Z","subjects":["signal processing","speech analysis"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-51482010109603140"],"render_values":[{"text":"etd-51482010109603140","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/36769","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Wicks, Alfred L."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Saunders, William R.","Burdisso, Ricardo A."]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Wilson, Leslie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T20:51:45Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T20:51:45Z","2003-06-25"]},{"key":"dc:date.issued","label":"Date","values":["1996-11-01"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["signal processing","speech analysis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-51482010109603140"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/36769"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Ever wonder why two people can sing the same note with the same loudness, but sound completely different? Middle C is middle C no matter who sings it, yet for some reason Lucianno Pavarotti1s middle C sounds richer and more beautiful than Bob Dylan1s middle C, for example. But then again, what is beauty in singing? It is a completely biased and abstract concept. To some, Bob Dylan1s voice may epitomize tonal beauty, while to others his voice may be comparable to fingernails on a chalk board. Anyway, differences in tone quality, or timbre, are due to differences in the spectral characteristics in different voices. The Music Muse is a computer program designed to help singers train their voices by showing them the individual components of their voices that combine to produce timbre. In paintings, many colors are combined to produce different hues and shades of color. The individual colors that make up the hue are difficult to distinguish. Similarly in music, harmonics with varying amplitudes combine to create voice colors, or timbres. These individual harmonics are difficult to distinguish by the ear alone. The Music Muse splits the voice up into its harmonic components by means of a Fourier transform. The transformed data is then plotted on a harmonic spectrum, from which singers can observe the number of harmonics in their tone, and their amplitudes relative to one another. It is these spectral characteristics that are important to voice timbre. The amplitudes of the harmonics in a voiced tone are determined by the resonant frequencies of the vocal tract. These resonances are called formants. When a harmonic that is produced by the vocal cords has a frequency that is at or near a formant frequency, it is amplified. Formants are determined by the length, size, and shape of the vocal tract. These parameters differ from person to person, and change during articulation. Optimal tonal quality during singing is obtained by placing formants at a desired frequency. The Music Muse calculates the formants of the voice by means of cepstral analysis. The formants are then plotted. With this tool, singers can learn how to place their formants. One of the difficulties of voice training is that singing is rated on a scale of quality, which is difficult to quantify. Also, feedback tends to be biased, and therefore subjective in nature. The Music Muse provides singers with the technology to quantify quality to a degree that makes it less of an abstract concept, and therefore more attainable."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["The Music Muse"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Wicks, Alfred L."],"dc:contributor.committeemember":["Saunders, William R.","Burdisso, Ricardo A."],"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Wilson, Leslie"],"dc:date.accessioned":["2014-03-14T20:51:45Z"],"dc:date.available":["2014-03-14T20:51:45Z","2003-06-25"],"dc:date.issued":["1996-11-01"],"dc:description.abstract":["Ever wonder why two people can sing the same note with the same loudness, but sound completely different? Middle C is middle C no matter who sings it, yet for some reason Lucianno Pavarotti1s middle C sounds richer and more beautiful than Bob Dylan1s middle C, for example. But then again, what is beauty in singing? It is a completely biased and abstract concept. To some, Bob Dylan1s voice may epitomize tonal beauty, while to others his voice may be comparable to fingernails on a chalk board. Anyway, differences in tone quality, or timbre, are due to differences in the spectral characteristics in different voices. The Music Muse is a computer program designed to help singers train their voices by showing them the individual components of their voices that combine to produce timbre. In paintings, many colors are combined to produce different hues and shades of color. The individual colors that make up the hue are difficult to distinguish. Similarly in music, harmonics with varying amplitudes combine to create voice colors, or timbres. These individual harmonics are difficult to distinguish by the ear alone. The Music Muse splits the voice up into its harmonic components by means of a Fourier transform. The transformed data is then plotted on a harmonic spectrum, from which singers can observe the number of harmonics in their tone, and their amplitudes relative to one another. It is these spectral characteristics that are important to voice timbre. The amplitudes of the harmonics in a voiced tone are determined by the resonant frequencies of the vocal tract. These resonances are called formants. When a harmonic that is produced by the vocal cords has a frequency that is at or near a formant frequency, it is amplified. Formants are determined by the length, size, and shape of the vocal tract. These parameters differ from person to person, and change during articulation. Optimal tonal quality during singing is obtained by placing formants at a desired frequency. The Music Muse calculates the formants of the voice by means of cepstral analysis. The formants are then plotted. With this tool, singers can learn how to place their formants. One of the difficulties of voice training is that singing is rated on a scale of quality, which is difficult to quantify. Also, feedback tends to be biased, and therefore subjective in nature. The Music Muse provides singers with the technology to quantify quality to a degree that makes it less of an abstract concept, and therefore more attainable."],"dc:description.degree":["Master of Science"],"dc:identifier.other":["etd-51482010109603140"],"dc:identifier.uri":["http://hdl.handle.net/10919/36769"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["signal processing","speech analysis"],"dc:title":["The Music Muse"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:37Z"}