Combining Audio-based Similarity with Web-based Data to Accelerate Automatic Music Playlist Generation
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
8th ACM SIGMM International Workshop on Multimedia Information Retrieval (MIR'06),
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
We present a technique for combining audio signal-based
music similarity with web-based musical artist similarity to
accelerate the task of automatic playlist generation. We
demonstrate the applicability of our proposed method by
extending a recently published interface for music players
that benefits from intelligent structuring of audio collections.
While the original approach involves the calculation of similarities
between every pair of songs in a collection, we incorporate
web-based data to reduce the number of necessary
similarity calculations. More precisely, we exploit artist similarity
determined automatically by means of web retrieval
to avoid similarity calculation between tracks of dissimilar
and/or unrelated artists. We evaluate our acceleration technique
on two audio collections with different characteristics.
It turns out that the proposed combination of audio- and
text-based similarity not only reduces the number of necessary
calculations considerably but also yields better results,
in terms of musical quality, than the initial approach
based on audio data only. Additionally, we conducted a
small user study that further confirms the quality of the
resulting playlists
Forschungs-