Adding voicing and auditory features and adapting solo-singing models with limited polyphonic data reduces alignment errors for lyrics in polyphonic audio.
A Hybrid of Deep Audio Feature and i-vector for Artist Recognition
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
Artist recognition is a task of modeling the artist's musical style. This problem is challenging because there is no clear standard. We propose a hybrid method of the generative model i-vector and the discriminative model deep convolutional neural network. We show that this approach achieves state-of-the-art performance by complementing each other. In addition, we briefly explain the advantages and disadvantages of each approach.
fields
eess.AS 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Acoustic Modeling for Automatic Lyrics-to-Audio Alignment
Adding voicing and auditory features and adapting solo-singing models with limited polyphonic data reduces alignment errors for lyrics in polyphonic audio.