Genre Identification

Genre identification, the task of automatically classifying text or multimedia content into predefined genres, aims to improve information retrieval and organization across diverse media. Current research focuses on leveraging transformer-based models, such as BERT and XLM-RoBERTa, and exploring multi-modal approaches that integrate audio, visual, and textual features for improved accuracy, particularly in challenging scenarios like cross-lingual or domain transfer. This field is significant for its applications in various domains, including music information retrieval, film recommendation systems, and the development of more robust and efficient text classification methods, potentially reducing the need for extensive manual annotation.