New Speech Enhancement Approach for Formant Evolution Detection

Abstract. Spectra is usually shown as a two-dimensional graph where colors are directly related to signal levels. A great deal of speech recognition work and research takes this type of parameter directly. In this paper we propose to combine typical signal level values with the vectorial components of a Slope matrix containing orientation information on spectra surfaces. This additional information will enable us to obtain an enhanced speech signal spectra as well as formant evolution detection and a matching method to compare speech spectra sections. The mathematical formalization is based on vector analysis and matrix operations, where the basic components are the normal vectors to a set of triangular surfaces covering the spectral values. This formalism enables the use of mathematical tools (Matlab or similar) in a very easy way; and from here it is possible to program algorithms and visualize the results efficiently.