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README.md
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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The data was generated using synthetic voices, and no real-world speakers are associated with the content. All voices were created through TTS systems, using speaker embeddings derived from publicly available corpora.
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### Annotations [optional]
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#### Annotation process
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<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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Annotations were applied manually to label whether a given audio clip contains misinformation. The annotation process followed strict guidelines, and multiple annotators verified the accuracy of the labels.
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#### Who are the annotators?
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<!-- This section describes the people or systems who created the annotations. -->
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The annotators were experts in misinformation detection, working under supervised conditions to ensure the integrity of the labels.
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#### Personal and Sensitive Information
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private. -->
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This dataset does not contain any personal or sensitive information. All audio samples are synthetic and not derived from real individuals.
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## Bias, Risks, and Limitations
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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The data was generated using synthetic voices, and no real-world speakers are associated with the content. All voices were created through TTS systems, using speaker embeddings derived from publicly available corpora.
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## Bias, Risks, and Limitations
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