Abstract
Fully automatic opera tracking is challenging because of the acoustic complexity of the genre, combining musical and linguistic information (singing, speech) in complex ways. In this paper, we propose a new pipeline for complete opera tracking. The pipeline is based on two trackers. A music tracker that has proven to be effective at tracking orchestral parts, will lead the tracking process. In addition, a lyrics tracker, that has recently been shown to reliably track the lyrics of opera songs, will correct the music tracker when tracking parts that have a text dominance over the music. We will demonstrate the efficiency of this method on the opera Don Giovanni, showing that this technique helps improving accuracy and robustness of a complete opera tracker.
| Originalsprache | Englisch |
|---|---|
| Titel | Proceedings of the 2nd Workshop on NLP for Music and Audio (NLP4MusA) |
| Seitenumfang | 5 |
| Publikationsstatus | Veröffentlicht - 2021 |
Wissenschaftszweige
- 202002 Audiovisuelle Medien
- 102 Informatik
- 102001 Artificial Intelligence
- 102003 Bildverarbeitung
- 102015 Informationssysteme
JKU-Schwerpunkte
- Digital Transformation
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