| Paper ID | SPE-53.5 |
| Paper Title |
A COMPARISON STUDY ON INFANT-PARENT VOICE DIARIZATION |
| Authors |
Junzhe Zhu, Mark Hasegawa-Johnson, Nancy McElwain, University of Illinois at Urbana-Champaign, United States |
| Session | SPE-53: Speaker Diarization |
| Location | Gather.Town |
| Session Time: | Friday, 11 June, 13:00 - 13:45 |
| Presentation Time: | Friday, 11 June, 13:00 - 13:45 |
| Presentation |
Poster
|
| Topic |
Speech Processing: [SPE-SPKR] Speaker Recognition and Characterization |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
We design a framework for studying prelinguistic child voice from 3 to 24 months based on state-of-the-art algorithms in diarization. Our system consists of a time-invariant feature extractor, a context-dependent embedding generator, and a classifier. We study the effect of swapping out different components of the system, as well as changing loss function, to find the best performance. We also present a multiple-instance learning technique that allows us to pre-train our parameters on larger datasets with coarser segment boundary labels. We found that our best system achieved 43.8% DER on test dataset, compared to 55.4% DER achieved by LENA software. We also found that using convolutional feature extractor instead of logmel features significantly increases the performance of neural diarization. |
