Static features in isolated vowel recognition at high pitch

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2008

Autores

Aníbal Ferreira (Autor) FEUP

Ata de Conferência Internacional

Título: SIGMAP 2008: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND MULTIMEDIA APPLICATIONS

Páginas: 63-68

International Conference on Signal Processing and Multimedia Applications

Oproto, PORTUGAL, JUL 26, 2008

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-004-4V3

Abstract (EN): Vowel recognition is frequently based on Linear Prediction (LP) analysis and formant estimation techniques. However, the performance of these techniques decreases in the case of female or child speech because at high pitch frequencies (F0) the magnitude spectrum is scarcely sampled making formant estimation unreliable. In this paper we describe the implementation of a perceptually motivated concept of vowel recognition that is based on Perceptual Spectral Clusters (PSC) of harmonic partials. PSC based features were evaluated in automatic recognition tests using the Mahalanobis distance and using a data base of five natural Portuguese vowel sounds uttered by 44 speakers, 27 of whom are child speakers. LP based features and Mel-Frequency Cepstral Coefficients (MFCC) were also included in the tests as a reference. Results show that while the recognition performance of PSC features falls between that of LP based features and that of MFCC coefficients, the normalization of PSC features by F0 increases the performance and approaches that of MFCC coefficients. PSC features are not only amenable to a psychophysical interpretation (as LP based features are) but have also the potential to compete with global shape features such as MFCCs.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6