Kacprzak, S., & Kowalczyk, K. (2024). HeightCeleb--an enrichment of VoxCeleb dataset with speaker height information. arXiv preprint arXiv:2410.12668.
This paper introduces HeightCeleb, a new dataset that adds speaker height information to the VoxCeleb dataset, aiming to address the lack of freely available, large-scale datasets for speaker height estimation research.
The researchers collected height information for 1251 speakers in the VoxCeleb dataset by querying Google Search, IMDB, and celebheights.com. They then analyzed the collected data and compared its statistical properties (mean, median, standard deviation, minimum, maximum) to existing datasets with height annotations, namely TIMIT and NISP. Finally, they demonstrated the potential of HeightCeleb by training simple regression models (MLR and PLSR) on the dataset using pre-trained ECAPA-TDNN speaker embeddings and evaluating their performance on TIMIT and HeightCeleb test sets.
HeightCeleb serves as a valuable resource for advancing research on speaker height estimation from speech, despite potential limitations in data accuracy. The authors encourage the development of more robust height estimation methods and emphasize the importance of evaluating error distributions beyond simple metrics like MAE and RMSE.
This research contributes a valuable resource to the field of speaker recognition and speech processing by providing a large-scale dataset for speaker height estimation. It also highlights the challenges and considerations associated with collecting and utilizing potentially inaccurate data for research purposes.
The study acknowledges the potential inaccuracies in the collected height data and suggests further research on improving data reliability. Future work could explore more sophisticated height estimation models and evaluate their performance on a gold standard dataset with precise height measurements. Additionally, investigating the ethical implications of using estimated personal attributes like height is crucial.
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by Stan... om arxiv.org 10-17-2024
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