Please login using the form on menu list.|
It is required to login for Full-Text PDF.
Speech Emotion Recognition Based on Parametric Filter and Fractal Dimension
IEICE TRANSACTIONS on Information and Systems Vol.E93-D No.8 pp.2324-2326
Publication Date: 2010/08/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
Full Text: PDF
In this paper, we propose a new method that employs two novel features, correlation density (Cd) and fractal dimension (Fd), to recognize emotional states contained in speech. The former feature obtained by a list of parametric filters reflects the broad frequency components and the fine structure of lower frequency components, contributed by unvoiced phones and voiced phones, respectively; the latter feature indicates the non-linearity and self-similarity of a speech signal. Comparative experiments based on Hidden Markov Model and K Nearest Neighbor methods are carried out. The results show that Cd and Fd are much more closely related with emotional expression than the features commonly used.