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Implementation of a monophonic note tracking algorithm on Android

机译:在Android中实现单声道音符跟踪算法

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Pitch tracking algorithms have been proposed in many digital speech processing literature. Among the practical use of pitch tracking are: improved recognition, improved speech synthesis, and semantic disambiguation. A similar problem to pitch tracking when applied to music input signals, is note tracking, i.e. detecting all the notes in the perceived music. The general problem of music recognition seems to be beyond the techniques that have been accomplished by the advances in digital speech processing. A “real music” signal is composed of multiple sound from several instruments, and digitally separating the mix into individual channels/tracks is a hard problem to solve. The algorithm described in this paper assumes that the input signal is produced by a single source and further it focuses on monophonic sound, as opposed to polyphonic sound where two or more notes are played at the same time. The algorithm described below has been implemented on an Android device using proper building blocks (Activity and Service) that comply with the Android design guidelines to achieve the best performance. In addition to the standard Android libraries from the latest Android SDK, the application also relies on a third-party library for digital signal processing routines. The Android implementation of the algorithm has been tested using input sources from human voice and musical instruments. The paper also shows the experimental results of handling these input sources.
机译:在许多数字语音处理文献中提出了节距跟踪算法。间距跟踪的实际用途是:改善识别,改善语音合成和语义消化觉。在应用于音乐输入信号时俯仰跟踪的类似问题是音符跟踪,即检测感知音乐中的所有音符。音乐识别的一般问题似乎超出了数字语音处理的进步所完成的技术。 “真实音乐”信号由多个仪器的多个声音组成,并将混合数字分离成各个通道/轨道是一个难以解决的问题。本文描述的算法假设输入信号由单个源产生,并且进一步聚焦在单声道声音上,而不是同时播放两个或更多个音符的多学声音。下面描述的算法已经在Android设备上实现了使用适当的构建块(活动和服务)来实现,符合Android设计指南以实现最佳性能。除了来自最新的Android SDK的标准Android库之外,应用程序还依赖于数字信号处理例程的第三方库。算法的Android实现已经使用来自人类语音和乐器的输入来源进行了测试。本文还显示了处理这些输入来源的实验结果。

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