| Revue: | Computación y sistemas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000411079 |
| ISSN: | 1405-5546 |
| Autores: | Patra, Braja Gopal1 Das, Dipankar1 Bandyopadhyay, Sivaji1 |
| Instituciones: | 1Jadavpur University, Department of Computer Science and Information Engineering, Calcuta, Bengala Occidental. India |
| Año: | 2016 |
| Periodo: | Jul-Sep |
| Volumen: | 20 |
| Número: | 3 |
| Paginación: | 515-526 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | Music information retrieval is currently an active domain of research. An interesting aspect of music information retrieval involves mood classification. While the Western music captured much attention, research on Indian music was limited and mostly based on audio data. In this work, the authors propose a mood taxonomy and describe the framework for developing a multimodal dataset (audio and lyrics) for Hindi songs. We observed differences in mood for several instances of Hindi songs while annotating the audio of such songs in contrast to their corresponding lyrics. Finally, the mood classification frameworks were developed for Hindi songs and they consist of three different systems based on the features of audio, lyrics and both. The mood classification systems based on audio and lyrics achieved F-measures of 58.2% and 55.1%, respectively whereas the multimodal system (combination of both audio and lyrics) achieved the maximum F-measure of 68.6% |
| Disciplinas: | Ciencias de la computación, Literatura y lingüística |
| Palabras clave: | Procesamiento de datos, Lingüística aplicada, Lingüística computacional, Canciones, Música hindi, Clasificación del humor, Ficheros multimodales |
| Keyword: | Computer science, Literature and linguistics, Data processing, Applied linguistics, Computing linguistics, Songs, Hindi music, Mood classification, Multimodal datasets |
| Texte intégral: | Texto completo (Ver HTML) |
