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A multi-frame blocking for signal segmentation in voice command recognition

机译:语音命令识别中信号分割的多帧阻塞

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Frame blocking segment the voice signals into overlapping frames to ensure information is maintained. Various sound features in the time domain can be extracted from the signal representation in the form of this frame. The frame blocking stage allows spectral distortion to appear at the beginning and the end of each frame, which gives rise to discontinuous signal pieces. It will appear as part of the voice feature if extracted directly in the time domain. In the frequency domain, these discontinuous signal pieces are removed using windowing techniques. However, the use of windowing techniques sometimes has an impact on changing signal information at the beginning and the end of the frame. This study proposes a multi-frame blocking method to optimize the frame blocking stage. The aim of the proposed method is to maintain the integrity of the signal information while minimizing the number of frames without losing information. In this study, the sample of the voice signal is a command signal used to control the basic movements of the robot. The absolute portion of PSD (Power Spectral Density) have used as a voice signal feature where the average values represented as grayscale images. The results of studies have shown an increase in the performance of the voice signal recognition stage by 18.29% when compared to using only conventional frame blocking methods.
机译:帧阻塞将语音信号分割为重叠的帧,以确保信息得到维护。可以从该帧形式的信号表示中提取时域中的各种声音特征。帧阻塞阶段允许频谱失真出现在每个帧的开始和结尾,这会引起不连续的信号片段。如果直接在时域中提取,它将显示为语音功能的一部分。在频域中,使用开窗技术将这些不连续的信号片段去除。然而,开窗技术的使用有时会影响在帧的开始和结束处改变信号信息。这项研究提出了一种多帧阻塞方法来优化帧阻塞阶段。所提出的方法的目的是在保持信号信息的完整性的同时最小化帧数而不会丢失信息。在这项研究中,语音信号的样本是用于控制机器人基本动作的命令信号。 PSD(功率谱密度)的绝对部分已用作语音信号特征,其中平均值表示为灰度图像。研究结果表明,与仅使用常规帧阻止方法相比,语音信号识别阶段的性能提高了18.29%。

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