This paper presents VoxCeleb-ESP, a new speaker recognition dataset that focuses on the Spanish language. The goal of this dataset is to capture real-world scenarios and incorporate diverse speaking styles, noises, and channel distortions. By doing so, it aims to provide a comprehensive and diverse dataset for speaker recognition tasks in the Spanish language.
VoxCeleb-ESP includes 160 Spanish celebrities from various categories, ensuring a representative distribution across age groups and geographic regions in Spain. This diverse set of speakers will help in training and evaluating speaker recognition models that can handle different accents, dialects, and speaking styles present in the Spanish language.
Speaker Trial Lists for Speaker Identification Tasks
In addition to the dataset itself, VoxCeleb-ESP provides two speaker trial lists for speaker identification tasks. These trial lists consist of target trials, where speakers are either from the same video or different videos. This allows for testing the performance of speaker identification models in both scenarios.
Furthermore, the paper also includes a cross-lingual evaluation of ResNet pretrained models. This evaluation helps to assess the generalizability and effectiveness of existing models trained on other languages when applied to the VoxCeleb-ESP dataset.
Preliminary Results and Implications
The preliminary results of speaker identification tasks using VoxCeleb-ESP are promising. They suggest that the complexity of the detection task in VoxCeleb-ESP is equivalent to that of the original and much larger VoxCeleb dataset in English. This is an important finding as it demonstrates that VoxCeleb-ESP can provide a challenging benchmark for evaluating speaker recognition models specifically designed for the Spanish language.
With the introduction of VoxCeleb-ESP, the field of speaker recognition benchmarks expands to include a comprehensive and diverse dataset specifically designed for the Spanish language. This will enable researchers and developers to train and evaluate their speaker recognition models on a more representative dataset, leading to more reliable and accurate performance when applied to real-world scenarios in Spanish-speaking regions.
“The introduction of VoxCeleb-ESP is a significant step forward in the field of speaker recognition. By focusing on the Spanish language and incorporating real-world scenarios, it provides a much-needed resource for training and evaluating speaker recognition models for Spanish speakers. I anticipate that this dataset will not only encourage further research in this area but also lead to advancements in speaker recognition technology for the Spanish language.”