Paper Info
Title
A Robust Audio Similarity Estimation Method for Audio Alignment in Mobile Karaoke Apps
Abstract
With smartphones further integrating into our lives, more people start to sing using mobile karaoke apps instead of going to a KTV club. However, the playback and record APIs of Android systems do not respond in real-time when called. Thus, an Android karaoke app will have to align the record music and the original accompaniment when super-posing those two audios. Dynamic time warping (DTW) based algorithms are usually used to find the optimal alignment between two audios and yield best result so far. In this paper, we propose a simple yet robust approach by considering waveform similarities to solve this problem. Experimental results show that our method outperforms the state-of-the-art method in both accuracy and robustness across different genres and devices.
Year
DOI
Venue
2014
10.1145/2578726.2578802
ICMR
Keywords
Field
DocType
mobile karaoke,robust audio similarity estimation,mobile karaoke apps,dynamic time warping,different genre,audio alignment,best result,record apis,record music,android system,ktv club,state-of-the-art method,user experience
User experience design,Android (operating system),Dynamic time warping,Computer science,Waveform,Robustness (computer science),Speech recognition
Conference
Citations 
PageRank 
References 
0
0.34
8
Authors
3
Name
Order
Citations
PageRank
Jinghui Mo11073.63
Yansong Feng273564.17
Dongyan Zhao399896.35