کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
406560 678096 2014 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Non-linear speech representation based on local predictability exponents
ترجمه فارسی عنوان
ارائه سخنرانی غیر خطی بر اساس شاخص های پیش بینی پذیری محلی
کلمات کلیدی
پردازش گفتار غیر خطی، پردازش سیگنال چند منظوره، سیگنال های پیچیده و سیستم
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

Looking for new perspectives to analyze non-linear dynamics of speech, this paper presents a novel approach based on a microcanonical multiscale formulation which allows the geometric and statistical description of multiscale properties of the complex dynamics. Speech is a complex system whose dynamics can be, to some extent, geometrically and statistically accessed by the computation of Local Predictability Exponents (LPEs) unlocking the determination of the most informative subset (Most Singular Manifold or MSM), leading to associated compact representation and reconstruction. But the complex intertwining of different dynamics in speech (added to purely turbulent descriptions) suggests the definition of appropriate multiscale functionals that might influence the evaluation of LPEs, hence leading to more compact MSM. Consequently, by using the classical and generic Sauer/Allebach algorithm for signal reconstruction from irregularly spaced samples, we show that speech reconstruction of good quality can be achieved using MSM of low cardinality. Moreover, in order to further show the potential of the new methodology, we develop a simple and efficient waveform coder which achieves almost the same level of perceptual quality as a standard coder, while having a lower bit-rate.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 132, 20 May 2014, Pages 136–141
نویسندگان
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