Low intelligibility of narration or dialogue resulting from high background level is one of the most common complaints in broadcasting. Even when the intelligibility is not compromised, listeners may have personal preferences that differ from the mix being broadcast. Dialogue Enhancement (DE) enables the delivery of optimal dialogue mixing to each listener, be it in terms of intelligibility or for aesthetic preference. This makes DE one of the most promising applications of user interactivity enabled by object-based audio broadcasting, such as MPEG-H. This paper investigates the use of source separation methods to extract dialogue and background from the complex sound mixture for enabling object-based broadcasting when dialogue is not available from the production process, as for example, with legacy content. The presented source separation technology integrates several separation approaches with known limitations into a more powerful overall architecture. In addition, the paper evaluates the subjective benefit of DE using the Adjustment/Satisfaction Test in which the listeners made extensive use of the dialogue level personalization. The fact that the preferred dialogue level had a high variance among the listeners indicates the need for this functionality. Even when an imperfect separation result was used for enabling DE, the possibility for personalizing the dialogue level lead to increased listener satisfaction.
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