Abstract
In this work, we propose to use as source of speech information the Short-MelfrequencyCepstra Time Transform (SMCTT), c τ (t). The SMCTT studies the time properties at quefrency τ. Since the SMCTT signal, c τ (t), comes from a nonlinear transformation of the speech signal, s(t), it makes the STMCTT a potential signal with new properties in time, frequency, quefrency, etc. The goal of this work is to present the performance of the SMCTT signal when the SMCTT is applied to an Automatic Speech Recognition (ASR) task. Our experiment results show that important information is given by this SMCTT waveform, c τ (t).
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Nolazco-Flores, J.A. (2005). ASR Based on the Analasys of the Short-MelFrequencyCepstra Time Transform. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_88
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DOI: https://doi.org/10.1007/11579427_88
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