| Revista: | Polibits |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000355979 |
| ISSN: | 1870-9044 |
| Autores: | García Salas, Horacio Alberto1 Gelbukh, Alexander2 Calvo, Hiram1 Galindo Soria, Fernando |
| Instituciones: | 1Instituto Politécnico Nacional, Centro de Investigación en Computación, México, Distrito Federal. México 2Waseda University, Tokio. Japón |
| Año: | 2011 |
| Número: | 44 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Aplicado, descriptivo |
| Resumen en inglés | We propose a model to generate music following a linguistic approach. Musical melodies form the training corpus where each of them is considered a phrase of a language. Implementing an unsupervised technique we infer a grammar of this language. We do not use predefined rules. Music generation is based on music knowledge represented by probabilistic matrices, which we call evolutionary matrices because they are changing constantly, even while they are generating new compositions. We show that the information coded by these matrices can be represented at any time by a probabilistic grammar; however we keep the representation of matrices because they are easier to update, while it is possible to keep separated matrices for generation of different elements of expressivity such as velocity, changes of rhythm, or timbre, adding several elements of expressiveness to the automatically generated compositions. We present the melodies generated by our model to a group of subjects and they ranked our compositions among and sometimes above human composed melodies |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial, Música, Sistemas evolutivos, Matriz evolutiva, Gramática generativa, Computación afectiva |
| Keyword: | Computer science, Artificial intelligence, Music, Evolutionary systems, Evolutionary matrix, Generative grammar, Affective computing |
| Texto completo: | Texto completo (Ver HTML) |
