On Multi-scale Fourier Transform Analysis of Speech Signals
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Feature extraction is a key step in many machine learning and signal processing applications. For speech signals in particular, it is important to derive features that contain both the vocal characteristics of the speaker and the content of the speech. In ...
It is a classic problem to estimate continuous-time sparse signals, like point sources in a direction-of-arrival problem, or pulses in a time-of-flight measurement. The earliest occurrence is the estimation of sinusoids in time series using Prony's method. ...
Institute of Electrical and Electronics Engineers2017
The advent of statistical parametric speech synthesis has paved new ways to a unified framework for hidden Markov model (HMM) based text to speech synthesis (TTS) and automatic speech recognition (ASR). The techniques and advancements made in the field of ...
We address the classical problem of delta feature computation, and interpret the operation involved in terms of Savitzky-Golay (SG) filtering. Features such as the mel-frequency cepstral coefficients (MFCCs), obtained based on short-time spectra of the spe ...
We propose two new fast algorithms for the computation of the continuous Fourier series and the continuous Haar transform of rectilinear polygons such as those of mask layouts in optical lithography. These algorithms outperform their discrete counterparts ...
The advent of statistical parametric speech synthesis has paved new ways to a unified framework for hidden Markov model (HMM) based text to speech synthesis (TTS) and automatic speech recognition (ASR). The techniques and advancements made in the field of ...
Ecole Polytechnique Federale de Lausanne (EPFL)2012
We present a novel, accurate and fast algorithm to obtain Fourier series coecients from an IC layer whose description consists of rectilinear polygons on a plane, and how to implement it using o-the-shelf hardware components. Based on properties of Fourier ...
We propose a novel method for constructing wavelet transforms of functions defined on the vertices of an arbitrary finite weighted graph. Our approach is based on defining scaling using the the graph analogue of the Fourier domain, namely the spectral deco ...
In this work, we present a novel way of computing the continuous Haar, Fourier and cosine series coefficients of rectilinear polygons. We derive algorithms to compute the inner products with the continuous basis functions directly from the vertices of the ...
Frequency Domain Linear Prediction (FDLP) provides an efficient way to represent temporal envelopes of a signal using auto-regressive models. For the input speech signal, we use FDLP to estimate temporal trajectories of sub-band energy by applying linear p ...