8 citations · 24 across the 10 of their papers we have counts for
5 papers · 1 filter
Identification of potential Music Information Retrieval technologies for computer-aided jingju singing training
Rong Gong, Xavier Serra
Music Information Retrieval (MIR) technologies have been proven useful in assisting western classical singing training. Jingju (also known as Beijing or Peking opera) singing is di…
Creating an A Cappella Singing Audio Dataset for Automatic Jingju Singing Evaluation Research
Rong Gong, Rafael Caro Repetto, Xavier Serra
The data-driven computational research on automatic jingju (also known as Beijing or Peking opera) singing evaluation lacks a suitable and comprehensive a cappella singing audio da…
Audio to score matching by combining phonetic and duration information
Rong Gong, Jordi Pons, Xavier Serra
We approach the singing phrase audio to score matching problem by using phonetic and duration information - with a focus on studying the jingju a cappella singing case. We argue th…
Score-informed syllable segmentation for a cappella singing voice with convolutional neural networks
Jordi Pons, Rong Gong, Xavier Serra
This paper introduces a new score-informed method for the segmentation of jingju a cappella singing phrase into syllables. The proposed method estimates the most likely sequence of…
Timbre Analysis of Music Audio Signals with Convolutional Neural Networks
Jordi Pons, Olga Slizovskaia, Rong Gong +2
The focus of this work is to study how to efficiently tailor Convolutional Neural Networks (CNNs) towards learning timbre representations from log-mel magnitude spectrograms. We fi…