Title
Who Do I Sound Like? Showcasing Speaker Recognition Technology By Youtube Voice Search
Abstract
The popularization of science can often be disregarded by scientists as it may be challenging to put highly sophisticated research into words that general public can understand. This work aims to help presenting speaker recognition research to public by proposing a publicly appealing concept for showcasing recognition systems. We leverage data from YouTube and use it in a large-scale voice search web application that finds the celebrity voices that best match to the user's voice. The concept was tested in a public event as well as "in the wild" and the received feedback was mostly positive. The i-vector based speaker identification back end was found to be fast ( 665 ms per request) and had a high identification accuracy ( 93%) for the YouTube target speakers. To help other researchers to develop the idea further, we share the source codes of the web platform used for the demo at https://github.com/bilalsoomro/speech-demo-platform.
Year
DOI
Venue
2018
10.1109/icassp.2019.8683272
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Large-scale speaker identification, speaker ranking, public demo, VoxCeleb, web service
Speaker identification,World Wide Web,Source code,Computer science,Speaker recognition,Web application,Voice search
Journal
Volume
ISSN
Citations 
abs/1811.03293
1520-6149
1
PageRank 
References 
Authors
0.35
5
5
Name
Order
Citations
PageRank
Ville Vestman1296.42
Bilal Soomro210.69
Anssi Kanervisto3246.77
Ville Hautamäki438533.51
Tomi Kinnunen5132386.67