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TOWARDS INTELLIGENT STRING MATCHING IN QUERY-BY-HUMMING SYSTEMS

机译:在逐嗡嗡声系统中匹配智能字符串匹配

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In the last 5-10 years, there have been several attempts at the creation of a musical database that can be queried acoustically. The main problem hindering such efforts so far has been scalability, with limits of the frequently used three-character representation for melodic contour becoming apparent even at relatively small database sizes. Extending the contour representation to 24 semitone resolution would go a long way towards solving such problems, but applying current string matching methods to a 24 character alphabet would prove difficult at best, and human errors would be far more prevalent. Here we show that the vast majority of errors at this resolution, although more numerous, are quite predictable using current methods of probabilisic modeling. This is evidence which we hope opens the door to more intelligent forms of note matching.
机译:在过去的5 - 10年中,在创建音乐数据库时有几次尝试可以在声学上询问。到目前为止妨碍了这种努力的主要问题一直是可扩展性,即使在相对较小的数据库尺寸下,旋律轮廓的常用三个字符表示的常用三个字符表示的极限也是显而易见的。将轮廓表示扩展到24个半音分辨率将有很长的路要解决这些问题,但将当前的字符串匹配方法应用于24个字符的字母表,并最好地证明困难,人类错误将更为普遍。在这里,我们表明,使用当前概率建模的方法,这分辨率的绝大多数错误虽然更加众多。这是我们希望为更智能形式的便条匹配开辟门的证据。

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