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首页> 外文会议>IFIP First International Workshop on Entertainment Computing (IWEC 2002) May 14-17, 2002 Makuhari, Japan >SOUNDCOMPASS~(TM) - A FAST QUERY-BY-HUMMING SYSTEM USING MULTIDIMENSIONAL FEATURE VECTORS
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SOUNDCOMPASS~(TM) - A FAST QUERY-BY-HUMMING SYSTEM USING MULTIDIMENSIONAL FEATURE VECTORS

机译：SOUNDCOMPASS〜（TM）-使用多维特征向量的快速悍马查询系统

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摘要

Retrieval using sound information as queries for a music database is intuitive and very useful. However, it is difficult to use hummed tunes as queries because they are often unclear. Thus, the SoundCompass~(TM) music retrieval system employs a similarity retrieval technique to overcome this problem. The retrieval result is a ranked list of songs that are similar to the hummed tune. The most significant ways in which our system are superior to other query-by-humming systems are that 1) musical data is processed based on "beats" instead of "notes", and 2) the retrieval is done through the use of an index based on multi-dimensional feature vectors. These features allow the system to retrieve songs quickly and precisely even if erroneously hummed tunes are used as queries. The database currently holds over 10,000 songs, and the retrieval time is about one second. The system is able to recognize a song and rank it within the first five places on the retrieval list for about 70% of hummed tunes that are recognizable to human subjects as being a part of the song.
机译：使用声音信息作为音乐数据库的查询进行检索是直观且非常有用的。但是，很难将哼唱曲调用作查询，因为它们常常不清楚。因此，SoundCompass TM音乐检索系统采用相似性检索技术来克服该问题。检索结果是与嗡嗡声相似的歌曲的排名列表。我们的系统优于其他按嗡嗡声查询系统的最重要方式是：1）根据“节拍”而不是“音符”处理音乐数据，以及2）通过使用索引进行检索基于多维特征向量。这些功能使系统可以快速，准确地检索歌曲，即使将错误的嗡嗡声用作查询也是如此。该数据库目前拥有10,000余首歌曲，并且检索时间约为一秒钟。该系统能够识别一首歌曲，并将其排在检索列表的前五个位置中，以获取大约70％的嗡嗡曲调，这些嗡嗡声被人类受试者识别为歌曲的一部分。

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