Building and combining document and music spaces of songs are discussed for a new music recommendation application, which uses commonly read texts such as Web log as query input. The most important application of this flexible recommendation system is its music query-by-Webpage, from which a song that appropriately matches Webpage is automatically played. The key idea of the proposed system is to train a linear transformation between document and music spaces so that query documents can be mapped onto a music space in which similarities based on acoustic characteristics is represented.
The basic system has been trained using 2,650 pairs of song and review texts. Through experimental evaluations, we show the effectiveness of the system, which is three times better than the previous system. Web text as a training corpus and a bigram representation for the document vector are also investigated for the purpose of improving the system, and their effectiveness is also confirmed.
Bibliographic reference. Takahashi, Ryoei / Ohishi, Yasunori / Kitaoka, Norihide / Takeda, Kazuya (2008): "Building and combining document and music spaces for music query-by-webpage system", In INTERSPEECH-2008, 2020-2023.