Significance of Maximum Spectral Amplitude in Sub-bands for Spectral Envelope Estimation and Its Application to Statistical Parametric Speech Synthesis

نویسندگان

  • Sivanand Achanta
  • Anandaswarup Vadapalli
  • Sai Krishna Rallabandi
  • Suryakanth V. Gangashetty
چکیده

In this paper we propose a technique for spectral envelope estimation using maximum values in the sub-bands of Fourier magnitude spectrum (MSASB). Most other methods in the literature parametrize spectral envelope in cepstral domain such as Mel-generalized cepstrum etc. Such cepstral domain representations, although compact, are not readily interpretable. This difficulty is overcome by our method which parametrizes in the spectral domain itself. In our experiments, spectral envelope estimated using MSASB method was incorporated in the STRAIGHT vocoder. Both objective and subjective results of analysis-by-synthesis indicate that the proposed method is comparable to STRAIGHT. We also evaluate the effectiveness of the proposed parametrization in a statistical parametric speech synthesis framework using deep neural networks.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Speech Enhancement by MAP Spectral Amplitude Estimation Using a Super-Gaussian Speech Model

This contribution presents two spectral amplitude estimators for acoustical background noise suppression based on maximum a posteriori estimation and super-Gaussian statistical modelling of the speech DFT amplitudes. The probability density function of the speech spectral amplitude is modelled with a simple parametric function, which allows a high approximation accuracy for Laplaceor Gamma-dist...

متن کامل

Noise Reduction by Maximum a Posteriori Spectral Amplitude Estimation with Supergaussian Speech Modeling

ESTIMATION WITH SUPERGAUSSIAN SPEECH MODELING Thomas Lotter and Peter Vary Institute of Communication Systems and Data Processing ( ) Aachen University (RWTH), Templergraben 55, D-52056 Aachen, Germany E-mail: lotter vary @ind.rwth-aachen.de ABSTRACT This contribution presents a spectral amplitude estimator for acoustical background noise suppression based on maximum a posteriori estimation and...

متن کامل

Statistical parametric speech synthesis with joint estimation of acoustic and excitation model parameters

This paper describes a novel framework for statistical parametric speech synthesis in which statistical modeling of the speech waveform is performed through the joint estimation of acoustic and excitation model parameters. The proposed method combines extraction of spectral parameters, considered as hidden variables, and excitation signal modeling in a fashion similar to factor analyzed traject...

متن کامل

MAXENPER: a program for maximum entropy spectral estimation with assessment of statistical significance by the permutation test

The maximum entropy spectral estimator is widely used because of its high spectral resolution, but it lacks an easy procedure for evaluating the statistical significance of the spectral estimates. We implemented the non-parametric computer intensive permutation test in order to evaluate the statistical significance of the maximum entropy spectral estimates. There is the possibility of choosing ...

متن کامل

Spectral Estimation of Stationary Time Series: Recent Developments

Spectral analysis considers the problem of determining (the art of recovering) the spectral content (i.e., the distribution of power over frequency) of a stationary time series from a finite set of measurements, by means of either nonparametric or parametric techniques. This paper introduces the spectral analysis problem, motivates the definition of power spectral density functions, and reviews...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1508.00354  شماره 

صفحات  -

تاریخ انتشار 2015