2021 IEEE International Conference on Acoustics, Speech and Signal Processing
6-11 June 2021 • Toronto, Ontario, Canada
Extracting Knowledge from Information
| Paper ID | SPE-20.1 | ||
| Paper Title | PLAYING A PART: SPEAKER VERIFICATION AT THE MOVIES | ||
| Authors | Andrew Brown, Jaesung Huh, Arsha Nagrani, University of Oxford, United Kingdom; Joon Son Chung, Naver Corporation, South Korea; Andrew Zisserman, University of Oxford, United Kingdom | ||
| Session | SPE-20: Speaker Recognition 4: Applications | ||
| Location | Gather.Town | ||
| Session Time: | Wednesday, 09 June, 14:00 - 14:45 | ||
| Presentation Time: | Wednesday, 09 June, 14:00 - 14:45 | ||
| Presentation | Poster | ||
| Topic | Speech Processing: [SPE-SPKR] Speaker Recognition and Characterization | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | The goal of this work is to investigate the performance of popular speaker recognition models on speech segments from movies, where often actors intentionally disguise their voice to play a character. We make the following three contributions: (i) We collect a novel, challenging speaker recognition dataset called VoxMovies, with speech for 856 identities from almost 4000 movie clips. VoxMovies contains utterances with varying emotion, accents and background noise, and therefore comprises an entirely different domain to the interview-style, emotionally calm utterances in current speaker recognition datasets such as VoxCeleb; (ii) We provide a number of domain adaptation evaluation sets, and benchmark the performance of state-of-the-art speaker recognition models on these evaluation pairs. We demonstrate that both speaker verification and identification performance drops steeply on this new data, showing the challenge in transferring models across domains; and finally (iii) We show that simple domain adaptation paradigms improve performance, but there is still large room for improvement. | ||