Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach
Esta investigación tiene como propósito solucionar el problema de encontrar un “buen” bajo para acompañar una melodía y una batería, siguiendo la estructura del genero Rock Alternativo. El método de solución consta de varias etapas las cuales incluyen: determinar la tonalidad de la canción utilizand...
- Autores:
-
Zarta Barrera, Andrés Felipe
- Tipo de recurso:
- Fecha de publicación:
- 2016
- Institución:
- Escuela Colombiana de Ingeniería Julio Garavito
- Repositorio:
- Repositorio Institucional ECI
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.escuelaing.edu.co:001/2051
- Acceso en línea:
- https://repositorio.escuelaing.edu.co/handle/001/2051
- Palabra clave:
- Algoritmos de grafos
Sistemas estocásticos
Procesos estocásticos
Graph algorithms
Stochastic processes
Stochastic systems
Teoría de grafos - Investigaciones
Acordes - Algoritmos - Investigaciones
Análisis estocástico - Investigaciones
- Rights
- openAccess
- License
- http://purl.org/coar/access_right/c_abf2
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| dc.title.eng.fl_str_mv |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach |
| title |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach |
| spellingShingle |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach Algoritmos de grafos Sistemas estocásticos Procesos estocásticos Graph algorithms Stochastic processes Stochastic systems Teoría de grafos - Investigaciones Acordes - Algoritmos - Investigaciones Análisis estocástico - Investigaciones |
| title_short |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach |
| title_full |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach |
| title_fullStr |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach |
| title_full_unstemmed |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach |
| title_sort |
Bassline composition for alternative rock using SP and SDS algorithms, a multi-objective approach |
| dc.creator.fl_str_mv |
Zarta Barrera, Andrés Felipe |
| dc.contributor.advisor.none.fl_str_mv |
Velasco Rodríguez, Nubia Milena |
| dc.contributor.author.none.fl_str_mv |
Zarta Barrera, Andrés Felipe |
| dc.contributor.corporatename.spa.fl_str_mv |
Universidad de los Andes |
| dc.subject.armarc.spa.fl_str_mv |
Algoritmos de grafos Sistemas estocásticos Procesos estocásticos |
| topic |
Algoritmos de grafos Sistemas estocásticos Procesos estocásticos Graph algorithms Stochastic processes Stochastic systems Teoría de grafos - Investigaciones Acordes - Algoritmos - Investigaciones Análisis estocástico - Investigaciones |
| dc.subject.armarc.eng.fl_str_mv |
Graph algorithms Stochastic processes Stochastic systems |
| dc.subject.proposal.spa.fl_str_mv |
Teoría de grafos - Investigaciones Acordes - Algoritmos - Investigaciones Análisis estocástico - Investigaciones |
| description |
Esta investigación tiene como propósito solucionar el problema de encontrar un “buen” bajo para acompañar una melodía y una batería, siguiendo la estructura del genero Rock Alternativo. El método de solución consta de varias etapas las cuales incluyen: determinar la tonalidad de la canción utilizando un algoritmo de Matching que compara las notas en la melodía con las notas en cada tonalidad, ajustar acordes a la melodía construyendo un grafo de posibles progresiones y encontrando la ruta mas corta en este, improvisar bajos usando estos acordes como guía utilizando el algoritmo “Stochastic Diffusion Search”. Las soluciones deben satisfacer una serie de restricciones mientras se maximiza la calidad del sonido medida usando dos criterios diferentes. |
| publishDate |
2016 |
| dc.date.issued.none.fl_str_mv |
2016 |
| dc.date.accessioned.none.fl_str_mv |
2022-05-06T18:19:51Z |
| dc.date.available.none.fl_str_mv |
2022-05-06T18:19:51Z |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/publishedVersion |
| dc.type.content.spa.fl_str_mv |
Text |
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info:eu-repo/semantics/masterThesis |
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http://purl.org/redcol/resource_type/ART |
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publishedVersion |
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https://repositorio.escuelaing.edu.co/handle/001/2051 |
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https://repositorio.escuelaing.edu.co/handle/001/2051 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.relation.indexed.spa.fl_str_mv |
N/A |
| dc.relation.references.spa.fl_str_mv |
Alfonseca, M., Cebrián, M., & Ortega, A. (2007). A Simple Genetic Algorithm for Music Generation by means of Algorithmic Information Theory. IEEE Congress on Evolutionary Computation . Bassinplace. (1 de December de 2008). The kick drums relation to the bass? TalkBass Forums. Dostál, M. (2005). GENETIC ALGORITHMS AS A MODEL OF MUSICAL CREATIVITY – ON GENERATING OF A HUMAN-LIKE RHYTHMIC ACCOMPANIMENT. olomouc: Palack ́y University . Dubnov, S., Assayag, G., Lartillot, O., & Bejerano, G. (2003). Using Machine-Learning Methods for Musical Style Modeling. IEEE Computer Society. Geem, Z., & Choi, J.-Y. (2007). Music Composition Using Harmony Search Algorithm. Springer. Herremans , D., Weisser, Sorensen, K., & Conklin. (2015). Generating structured music for bagana using quality metrics based on Markov models. ELSEVIER. Herremans, D., & Sorensen, K. (2013). Composing fifth species counterpoint music with a variable neighborhood search algorithm. Antwerp: ELSEVIER. Herremans, D., Martens, D., & Sorensen, K. (2014). Dance Hit Song Prediction. Antwerp: ANT/OR. Kunimatsu, K., Ishikawa, Y., Takata, M., & Joe, K. (2015). A Music Composition Model with Genetic Programming –A Case Study of Chord Progression and Bassline-. Nara. Laine, P., & Kuuskankare, M. (1994). Genetic Algorithms in Musical Style oriented Generation. Helsinki: Sibelius Acadmy Computer Music Studio. Lichtenwalter, R., Zorina, K., & Chawla, N. (2008). Applying Learning Algorithms to Music Generation. López-Ortega, O., & López-Popa, S. I. (2012). Fractals, fuzzy logic and expert systems to assist in the construction of musical pieces . Hidalgo: ELSEVIER. Lozano, L., Medaglia, A., & Velasco, N. (2009). Generation of Pop-Rock Chord Sequences Using Genetic Algorithms and Variable Neighborhood Search. Bogotá: Springer. Majid Al-Rifaie, A., & Majid Al-Rifaie, M. (2015). Generative Music with Stochastic Diffusion Search. London: SpringerLink. Ren, T., Wang, Y.-f., Du, D., Liu, M.-m., & Siddiqi, A. (2015). The guitar chord-generating algorithm based on complex network. Shenyang: ELSEVIER. Tojui, N., & Iba, H. (2000). Music Composition with Interactive Evolutionary Computation. Tokyo. |
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http://purl.org/coar/access_right/c_abf2 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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http://purl.org/coar/access_right/c_abf2 |
| dc.format.extent.spa.fl_str_mv |
14 páginas. |
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application/pdf |
| dc.publisher.spa.fl_str_mv |
Uniandes |
| dc.publisher.faculty.spa.fl_str_mv |
Facultad de Ingeniería |
| dc.publisher.place.spa.fl_str_mv |
Bogotá D.C. |
| dc.publisher.program.spa.fl_str_mv |
Maestría en Ingeniería Industrial |
| dc.source.spa.fl_str_mv |
https://repositorio.uniandes.edu.co/handle/1992/13894?show=full |
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Escuela Colombiana de Ingeniería Julio Garavito |
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Velasco Rodríguez, Nubia Milena60b26c05a1fd41a8796a2a23085a8d2f600Zarta Barrera, Andrés Felipeb4d87f84b115dfc10da9b77b0500c054600Universidad de los Andes2022-05-06T18:19:51Z2022-05-06T18:19:51Z2016https://repositorio.escuelaing.edu.co/handle/001/2051Esta investigación tiene como propósito solucionar el problema de encontrar un “buen” bajo para acompañar una melodía y una batería, siguiendo la estructura del genero Rock Alternativo. El método de solución consta de varias etapas las cuales incluyen: determinar la tonalidad de la canción utilizando un algoritmo de Matching que compara las notas en la melodía con las notas en cada tonalidad, ajustar acordes a la melodía construyendo un grafo de posibles progresiones y encontrando la ruta mas corta en este, improvisar bajos usando estos acordes como guía utilizando el algoritmo “Stochastic Diffusion Search”. Las soluciones deben satisfacer una serie de restricciones mientras se maximiza la calidad del sonido medida usando dos criterios diferentes.This research proposes a solution to the problem of finding a “good” bassline to accompany a melody and a drumbeat following the structure of the alternative rock genre. The solution method is made up of different steps which include: determining the key of the song by using a matching algorithm that compares the notes in the melody with the notes in each key, fitting chords to the melody by constructing a graph of possible progressions using candidate chords selected through a matching algorithm and finding the shortest path in it, improvising basslines using these chords as guidelines through the use of stochastic diffusion search algorithm. Solutions must satisfy constraints regarding their relationship with the drumbeat and the melody while maximizing the quality of the overall sound measured with two independent criteria.MaestríaMagíster en Ingeniería Industrial14 páginas.application/pdfengUniandesFacultad de IngenieríaBogotá D.C.Maestría en Ingeniería Industrialhttps://repositorio.uniandes.edu.co/handle/1992/13894?show=fullBassline composition for alternative rock using SP and SDS algorithms, a multi-objective approachTrabajo de grado - Maestríainfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/masterThesishttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85N/AAlfonseca, M., Cebrián, M., & Ortega, A. (2007). A Simple Genetic Algorithm for Music Generation by means of Algorithmic Information Theory. IEEE Congress on Evolutionary Computation .Bassinplace. (1 de December de 2008). The kick drums relation to the bass? TalkBass Forums.Dostál, M. (2005). GENETIC ALGORITHMS AS A MODEL OF MUSICAL CREATIVITY – ON GENERATING OF A HUMAN-LIKE RHYTHMIC ACCOMPANIMENT. olomouc: Palack ́y University .Dubnov, S., Assayag, G., Lartillot, O., & Bejerano, G. (2003). Using Machine-Learning Methods for Musical Style Modeling. IEEE Computer Society.Geem, Z., & Choi, J.-Y. (2007). Music Composition Using Harmony Search Algorithm. Springer.Herremans , D., Weisser, Sorensen, K., & Conklin. (2015). Generating structured music for bagana using quality metrics based on Markov models. ELSEVIER.Herremans, D., & Sorensen, K. (2013). Composing fifth species counterpoint music with a variable neighborhood search algorithm. Antwerp: ELSEVIER.Herremans, D., Martens, D., & Sorensen, K. (2014). Dance Hit Song Prediction. Antwerp: ANT/OR.Kunimatsu, K., Ishikawa, Y., Takata, M., & Joe, K. (2015). A Music Composition Model with Genetic Programming –A Case Study of Chord Progression and Bassline-. Nara.Laine, P., & Kuuskankare, M. (1994). Genetic Algorithms in Musical Style oriented Generation. Helsinki: Sibelius Acadmy Computer Music Studio.Lichtenwalter, R., Zorina, K., & Chawla, N. (2008). Applying Learning Algorithms to Music Generation.López-Ortega, O., & López-Popa, S. I. (2012). Fractals, fuzzy logic and expert systems to assist in the construction of musical pieces . Hidalgo: ELSEVIER.Lozano, L., Medaglia, A., & Velasco, N. (2009). Generation of Pop-Rock Chord Sequences Using Genetic Algorithms and Variable Neighborhood Search. Bogotá: Springer.Majid Al-Rifaie, A., & Majid Al-Rifaie, M. (2015). Generative Music with Stochastic Diffusion Search. London: SpringerLink.Ren, T., Wang, Y.-f., Du, D., Liu, M.-m., & Siddiqi, A. (2015). The guitar chord-generating algorithm based on complex network. Shenyang: ELSEVIER.Tojui, N., & Iba, H. (2000). Music Composition with Interactive Evolutionary Computation. Tokyo.info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Algoritmos de grafosSistemas estocásticosProcesos estocásticosGraph algorithmsStochastic processesStochastic systemsTeoría de grafos - InvestigacionesAcordes - Algoritmos - InvestigacionesAnálisis estocástico - InvestigacionesLICENSElicense.txtlicense.txttext/plain; charset=utf-81881https://repositorio.escuelaing.edu.co/bitstream/001/2051/2/license.txt5a7ca94c2e5326ee169f979d71d0f06eMD52open accessORIGINALZarta Barrera, Andrés Felipe.pdfZarta Barrera, Andrés Felipe.pdfBassline composition for alternative rock using SP and SDS algorithms, a multi-objective approachapplication/pdf1501182https://repositorio.escuelaing.edu.co/bitstream/001/2051/1/Zarta%20Barrera%2c%20Andr%c3%a9s%20Felipe.pdfa4d423fa05b0b5a94517ec3027e8953fMD51open accessTEXTBassline Composition for Alternative Rock using SP and SDS.pdf.txtBassline Composition for Alternative Rock using SP and SDS.pdf.txtExtracted texttext/plain48228https://repositorio.escuelaing.edu.co/bitstream/001/2051/3/Bassline%20Composition%20for%20Alternative%20Rock%20using%20SP%20and%20SDS.pdf.txt3a151d1e2ab30a3ea1f99529b912d691MD53open accessZarta Barrera, Andrés Felipe.pdf.txtZarta Barrera, Andrés Felipe.pdf.txtExtracted texttext/plain48228https://repositorio.escuelaing.edu.co/bitstream/001/2051/5/Zarta%20Barrera%2c%20Andr%c3%a9s%20Felipe.pdf.txt3a151d1e2ab30a3ea1f99529b912d691MD55open accessTHUMBNAILBassline Composition for Alternative Rock using SP and SDS.pdf.jpgBassline Composition for Alternative Rock using SP and SDS.pdf.jpgGenerated Thumbnailimage/jpeg15603https://repositorio.escuelaing.edu.co/bitstream/001/2051/4/Bassline%20Composition%20for%20Alternative%20Rock%20using%20SP%20and%20SDS.pdf.jpgf191eb9f43b6f9e973fd042bfe2f2c1dMD54open accessZarta Barrera, Andrés Felipe.pdf.jpgZarta Barrera, Andrés Felipe.pdf.jpgGenerated Thumbnailimage/jpeg15603https://repositorio.escuelaing.edu.co/bitstream/001/2051/6/Zarta%20Barrera%2c%20Andr%c3%a9s%20Felipe.pdf.jpgf191eb9f43b6f9e973fd042bfe2f2c1dMD56open access001/2051oai:repositorio.escuelaing.edu.co:001/20512022-08-13 03:00:39.016open accessRepositorio Escuela Colombiana de Ingeniería Julio Garavitorepositorio.eci@escuelaing.edu.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 |