mlsanityData to 7 Oct 2026

Speech-based Age and Gender Prediction with Transformers

arXiv 2306.16962 ↗First posted 29 Jun 2023cs.SD eess.AScited by 14

Not on the map. Why?

Abstract (arXiv)

We report on the curation of several publicly available datasets for age and gender prediction. Furthermore, we present experiments to predict age and gender with models based on a pre-trained wav2vec 2.0. Depending on the dataset, we achieve an MAE between 7.1 years and 10.8 years for age, and at least 91.1% ACC for gender (female, male, child). Compared to a modelling approach built on handcrafted features, our proposed system shows an improvement of 9% UAR for age and 4% UAR for gender. To make our findings reproducible, we release the best performing model to the community as well as the sample lists of the data splits.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jun 2023.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 10; 2026: 2.

14 papers.

Sort: