一种自由源法校准大口径传声器阵列

Sarthak Khanal, H. Silverman, Rahul R. Shakya
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引用次数: 15

摘要

大孔径麦克风阵列可用于捕获和增强来自嘈杂、多说话和混响环境中的单个说话者的语音。然而,他们必须校准,往往不止一次,以获得准确的三维坐标为所有的麦克风。直接测量技术,如使用卷尺或基于激光的工具,既麻烦又耗时。以前一些使用声信号进行阵列校准的方法需要笨重的硬件和/或固定的已知源位置。其他允许更灵活的源位置的方法,通常在实际数据上存在问题,只能报告2D的结果,或者只能用于小型阵列。本文描述了一种完整的、鲁棒的利用声信号进行自动校准的方法,该方法简单、可重复、准确,并已被证明适用于实际系统。该方法只需要一个换能器(扬声器),在其中心上方附加一个麦克风。该装置在麦克风阵列的焦点体积周围自由移动,从所有麦克风产生一个长录音。在那之后,系统是完全自动的。我们描述了自由源方法(FrSM),验证了其有效性,并根据实测的地面真值给出了精度结果。在实际的128个传声器阵列中,与其他几种方法进行了性能比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Free-Source Method (FrSM) for Calibrating a Large-Aperture Microphone Array
Large-aperture microphone arrays can be used to capture and enhance speech from individual talkers in noisy, multi-talker, and reverberant environments. However, they must be calibrated, often more than once, to obtain accurate 3-dimensional coordinates for all microphones. Direct-measurement techniques, such as using a measuring tape or a laser-based tool are cumbersome and time-consuming. Some previous methods that used acoustic signals for array calibration required bulky hardware and/or fixed, known source locations. Others, which allowed more flexible source placement, often have issues with real data, have reported results for 2D only, or work only for small arrays. This paper describes a complete and robust method for automatic calibration using acoustic signals which is simple, repeatable, accurate, and has been shown to work for a real system. The method requires only a single transducer (speaker) with a microphone attached above its center. The unit is freely moved around the focal volume of the microphone array generating a single long recording from all the microphones. After that, the system is completely automatic. We describe the free source method (FrSM), validate its effectiveness and present accuracy results against measured ground truth. The performance of FrSM is compared to that from several other methods for a real 128-microphone array.
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来源期刊
IEEE Transactions on Audio Speech and Language Processing
IEEE Transactions on Audio Speech and Language Processing 工程技术-工程:电子与电气
自引率
0.00%
发文量
0
审稿时长
24.0 months
期刊介绍: The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.
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