Mel-generalized cepstral analysis - a unified approach to speech spectral estimation

نویسندگان

  • Keiichi Tokuda
  • Takao Kobayashi
  • Takashi Masuko
  • Satoshi Imai
چکیده

The generalized cepstral analysis method is viewed as a unified approach to the cepstral method and the linear prediction method, in which the model spectrum varies continuously from all-pole to cepstral according to the value of a parameter γ. Since the human ear has high resolution at low frequencies, introducing similar characteristics to the model spectrum, we can represent speech spectrum more efficiently. From this point of view, this paper proposes a spectral estimation method which uses the spectral model represented by mel-generalized cepstral coefficients. The effectiveness of mel-generalized cepstral analysis is demonstrated by an experiment of HMM-based isolated word recognition.

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

A unified maximum likelihood approach to acoustic mismatch compensation: application to noisy Lombard speech recognition

In the context of continuous density hidden Markov model (CDHMM) we present a uni ed maximum likelihood (ML) approach to acoustic mismatch compensation. This is achieved by introducing additive Gaussian biases at the state level in both the mel cepstral and linear spectral domains. Flexible modelling of di erent mismatch e ects can be obtained through appropriate bias tying. A Maximum likelihoo...

متن کامل

A 16 kb/s Wideband CELP-Based Speech Coder Using Mel-Generalized Cepstral Analysis

We propose a wideband CELP-type speech coder at 16 kb/s based on a mel-generalized cepstral (MGC) analysis technique. MGC analysis makes it possible to obtain a more accurate representation of spectral zeros compared to linear predictive (LP) analysis and take a perceptual frequency scale into account. A major advantage of the proposed coder is that the benefits of MGC representation of speech ...

متن کامل

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

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 meth...

متن کامل

Feature extraction from higher-lag autocorrelation coefficients for robust speech recognition

In this paper, a feature extraction method that is robust to additive background noise is proposed for automatic speech recognition. Since the background noise corrupts the autocorrelation coefficients of the speech signal mostly at the lowertime lags, while the higher-lag autocorrelation coefficients are least affected, this method discards the lower-lag autocorrelation coefficients and uses o...

متن کامل

Mel-lp Based Generalized Cepstral Analysis for Noisy Speech Recognition Using Hmm

This paper deals with LP based Mel-Generalized cepstrum which has been used as front-end for Hidden Markov Model (HMM) based speech recognition and it incorporates equal-loudness power law as well as auditory-like frequency resolution. To utilize the generalized cepstral representation, the model spectrum can be varied continuously from the all-pole spectrum to that represented by the cepstrum ...

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:

دوره   شماره 

صفحات  -

تاریخ انتشار 1994