Improving Real-time Score Following in Opera by Combining Music with Lyrics Tracking

Charles Brazier, Gerhard Widmer

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

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.
Original languageEnglish
Title of host publicationProceedings of the 2nd Workshop on NLP for Music and Audio (NLP4MusA)
Number of pages5
Publication statusPublished - 2021

Fields of science

  • 202002 Audiovisual media
  • 102 Computer Sciences
  • 102001 Artificial intelligence
  • 102003 Image processing
  • 102015 Information systems

JKU Focus areas

  • Digital Transformation

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