The EMO dataset is a high-quality, paired audio corpus specifically developed to support research in vocal timbral technique conversion, with a primary focus on the vocal fry scream. It was created to address the significant scarcity of paired data for extreme vocalizations in the research community. Key Dataset Features: Content: A total of 1040 high-quality clips consisting of 520 modal voice and 520 vocal fry scream pairs. Duration: Approximately 42 min. Source: Recorded by a single professional metal singer. Languages: Includes vocalizations in both Chinese and English. Alignment: All clips were manually aligned within a Digital Audio Workstation to ensure precise temporal consistency between the modal and scream pairs.