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Found 5 papers, 0 papers with code
Towards Deep Modeling of Music Semantics using EEG Regularizers
Modeling of music audio semantics has been previously tackled through learning of mappings from audio data to high-level tags or latent unsupervised spaces.
An Information-theoretic Approach to Machine-oriented Music Summarization
Our results suggest that relative entropy is a good predictor of summarization performance in the context of tasks relying on a bag-of-features model.
Summarization of Films and Documentaries Based on Subtitles and Scripts
We assess the performance of generic text summarization algorithms applied to films and documentaries, using the well-known behavior of summarization of news articles as reference.
Using Generic Summarization to Improve Music Information Retrieval Tasks
We evaluate the summarization process on binary and multiclass music genre classification tasks, by comparing the performance obtained using summarized datasets against the performances obtained using continuous segments (which is the traditional method used for addressing the previously mentioned time constraints) and full songs of the same original dataset.
On the Application of Generic Summarization Algorithms to Music
Several generic summarization algorithms were developed in the past and successfully applied in fields such as text and speech summarization.
