This paper describes data collection efforts conducted as part of the
RedDots project which is dedicated to the study of speaker recognition
under conditions where test utterances are of short duration and of
variable phonetic content. At the current stage, we focus on English speakers, both native and non-native, recruited worldwide. This is made possible through the use of a recording front-end consisting of an application running on mobile devices communicating with a centralized web server at the back-end. Speech recordings are collected by having speakers read text prompts displayed on the screen of the mobile devices. We aim to collect a large number of sessions from each speaker over a long time span, typically one session per week over a one year period. The corpus is expected to include rich inter-speaker and intra-speaker variations, both intrinsic and extrinsic (that is, due to recording channel and acoustic environment).
Bibliographic reference. Lee, Kong Aik / Larcher, Anthony / Wang, Guangsen / Kenny, Patrick / Brümmer, Niko / Leeuwen, David van / Aronowitz, Hagai / Kockmann, Marcel / Vaquero, Carlos / Ma, Bin / Li, Haizhou / Stafylakis, Themos / Alam, Md. Jahangir / Swart, Albert / Perez, Javier (2015): "The reddots data collection for speaker recognition", In INTERSPEECH-2015, 2996-3000.