| Autor: |
Dzhambazov, Georgi, Yang, Yile, Repetto, Rafael Caro, Serra, Xavier |
| Rok vydání: |
2016 |
| Předmět: |
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| Zdroj: |
Papers |
| DOI: |
10.21427/d7gr04 |
| Popis: |
In this study we propose how to modify a standard approach for text-to-speech alignment to apply in the case of alignment of lyrics and singing voice. We model phoneme durations by means of a duration-explicit hidden Markov model (DHMM) phonetic recognizer based on MFCCs. The phoneme durations are empirically set in a probabilistic way, based on prior knowledge about the lyrics structure and metric principles, specific for the Beijing opera music tradition. Phoneme models are GMMs trained directly on a small corpus of annotated singing voice. The alignment is evaluated on a cappella material from Beijing opera, which is characterized by its particularly long syllable durations. Results show that the incorporation of music-specific knowledge results in a very high alignment accuracy, outperforming significantly a baseline HMM-based approach. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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