@inproceedings{filho-etal-2025-brspeech,
    title = "{BRS}peech-{DF}: A Deep Fake Synthetic Speech Dataset for {P}ortuguese Zero-Shot {TTS}",
    author = "Filho, Alexandre Costa Ferro  and
      Virgilli, Rafaello  and
      Souza, Lucas Alcantara  and
      de Oliveira, F S  and
      Ferreira, Marcelo Henrique Lopes  and
      Tunnermann, Daniel  and
      Oliveira, Gustavo Dos Reis  and
      Soares, Anderson Da Silva  and
      Galv{\~a}o Filho, Arlindo Rodrigues",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-main.1780/",
    pages = "35110--35115",
    ISBN = "979-8-89176-332-6",
    abstract = "The detection of audio deepfakes (ADD) has become increasingly important due to the rapid evolution of generative speech models. However, progress in this field remains uneven across languages, particularly for low-resource languages like Portuguese, which lack high-quality datasets. In this paper, we introduce BRSpeech-DF, the first publicly available ADD dataset for Portuguese, encompassing both Brazilian and European variants. The dataset contains over 458,000 utterances, including a smaller portion of real speech from 62 speakers and a large collection of synthetic samples generated using multiple zero-shot text-to-speech (TTS) models, each conditioned on the original speaker{'}s voice. By providing this resource, our objective is to support the development of robust, multilingual detection systems, thereby advancing equity in speech forensics and security research. BRSpeech-DF addresses a significant gap in annotated data for underrepresented languages, facilitating more inclusive and generalizable advancements in synthetic speech detection."
}