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SPECTRUM ANALYSIS OF SPEECH RECOGNITION VIA DISCRETE TCHEBICHEF TRANSFORM

机译:离散TCHEBICHEF变换在语音识别中的光谱分析

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摘要

Abstract-Speech recognition is still a growing field. It carries strong potential in the near future as computing power grows. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) is the traditional technique to analyze frequency spectrum of the signal in speech recognition. Speech recognition operation requires heavy computation due to large samples per window. In addition, FFT consists of complex field computing. This paper proposes an approach based on discrete orthonormal Tchebichef polynomials to analyze a vowel and a consonant in spectral frequency for speech recognition. The Discrete Tchebichef Transform (DTT) is used instead of popular FFT. The preliminary experimental results show that DTT has the potential to be a simpler and faster transformation for speech recognition.
机译:摘要语音识别仍然是一个不断发展的领域。随着计算能力的增长,它在不久的将来具有强大的潜力。频谱分析是语音识别中的基本操作。快速傅立叶变换(FFT)是在语音识别中分析信号频谱的传统技术。由于每个窗口的样本量大,语音识别操作需要大量的计算。此外,FFT包括复杂的现场计算。本文提出了一种基于离散正交Tchebichef多项式的方法来分析元音和频谱频率的辅音以进行语音识别。使用离散Tchebichef变换(DTT)代替了流行的FFT。初步的实验结果表明,DTT有可能成为语音识别的一种更简单,更快速的转换。

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