Cepstrum-based pitch detection using a new statistical V/UV classification algorithm

نویسندگان

  • Sassan Ahmadi
  • Andreas Spanias
چکیده

An improved cepstrum-based voicing detection and pitch determination algorithm is presented. Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech signal. Pitch frequency information is extracted by a modified cepstrum-based method and then carefully refined using pitch tracking, correction, and smoothing algorithms. Performance analysis on a large database indicates considerable improvement relative to the conventional cepstrum method. The proposed algorithm is also shown to be robust to additive noise.

برای دانلود رایگان 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 New Method of Voiced/Unvoiced Classification Based on Clustering

In this paper, a new method for making v/uv decision is developed which uses a multi-feature v/uv classification algorithm based on the analysis of cepstral peak, zero crossing rate, and autocorrelation function (ACF) peak of short-time segments of the speech signal by using some clustering methods. This v/uv classifier achieved excellent results for identification of voiced and unvoiced segmen...

متن کامل

Classification of Iranian Traditional Music Dastgahs Using Features Based on Pitch Frequency

The Iranian traditional music is composed of seven majors Dastgahs: Chahargah, Homayoun, Mahour, Segah, Shour, Nava, and Rast-Panjgah. In this paper, a new algorithm for the classification of the Iranian traditional music Dastgahs based on pitch frequency is proposed. In this algorithm, the features of Lagrange coefficients of pitch logarithm (LCPL), Fuzzy similarity sets type 2 (FSST2), and th...

متن کامل

A Pitch Detection Algorithm Based on Windowless Autocorrelation Function and Modified Cepstrum Method in Noisy Environments

This paper proposes a new pitch detection algorithm of speech signals in noisy environment. The performance of the cepstrum method is effected due to the formant effect and the presence of spurious peaks introduced in noisy condition. In our proposed method, we firstly employ windowless autocorrelation function instead of its speech signal for obtaining the cepstrum. The windowless autocorrelat...

متن کامل

GMM Classifier for Identification of Neurological Disordered Voices Using MFCC Features

Automatic detection of neurological disordered subjects voice mostly relies on parameters extracted from time-domain processing. The calculation of these parameters often requires prior pitch period estimation; which in turn depends heavily on the robustness of pitch detection algorithm. In the present work cepstraldomain processing technique which does not require pitch estimation has been ado...

متن کامل

Robust Pitch Detection Based on Recurrence Analysis and Empirical Mode Decomposition

A new pitch detection method is designed by the recurrence analysis in this paper, which is combined of Empirical Mode Decomposition (EMD) and Elliptic Filter (EF). The Empirical Mode Decomposition (EMD) of Hilbert-Huang Transform (HHT) is utilized tosolve the problem, and a noisy voice is first filtered on the elliptic band filter. The two Intrinsic Mode Functions (IMF) are synthesized by EMD ...

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

عنوان ژورنال:
  • IEEE Trans. Speech and Audio Processing

دوره 7  شماره 

صفحات  -

تاریخ انتشار 1999