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Implementation of a monophonic note tracking algorithm on Android

机译:单音笔记跟踪算法在Android上的实现

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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已经提出了音调跟踪算法。音调跟踪的实际用途包括:改进的识别,改进的语音合成和语义歧义消除。当应用于音乐输入信号时,与音高跟踪类似的问题是音符跟踪,即,检测所感知的音乐中的所有音符。音乐识别的一般问题似乎超出了数字语音处理技术的进步。 “真实的音乐”信号由来自多种乐器的多种声音组成,将混音数字化成单独的声道/音轨是一个很难解决的问题。本文中描述的算法假定输入信号是由单个源产生的,而且它专注于单音,而不是同时演奏两个或更多音符的多音。以下描述的算法已在Android设备上使用符合Android设计准则的最佳构建块(活动和服务)实现,以实现最佳性能。除了来自最新的Android SDK的标准Android库之外,该应用程序还依赖于第三方库来进行数字信号处理例程。已经使用人类语音和乐器的输入源对算法的Android实现进行了测试。本文还显示了处理这些输入源的实验结果。

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