Datasets for training generative AI models in voice modality are curated to include diverse, high-quality audio samples. They are labeled and segmented to provide contextual information for training. Preprocessing steps such as noise reduction, normalization, and sometimes augmentation are applied to enhance the dataset's quality and ensure effective model training.
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