Revisión de las Tecnologías y Aplicaciones del Habla Sub-vocal

This paper presents a review of the main applicative and methodological approaches that have been developed in recent years for sub-vocal speech or silent language. The sub-vocal speech can be defined as the identification and characterization of bioelectric signals that control the vocal tract, when is not produced sound production by the caller. The first section makes a deep review of methods for detecting silent language. In the second part are evaluated the technologies implemented in recent years, followed by a review of the main applications of this type of speech and finally present a broad comparison between jobs that have been developed in industry and academic applications.Este trabajo presenta una revisión de estado de las principales temáticas aplicativas y metodológicas del habla sub-vocal que se han venido desarrollando en los últimos años. La primera sección hace una honda revisión de los métodos de detección del lenguaje silencioso. En la segunda parte se evalúan las tecnologías implementadas en los últimos años, seguido de un análisis en las principales aplicaciones de este tipo de lenguaje y finalmente presentado una amplia comparación entre los trabajos que se han hecho en industria y academia utilizando este tipo de desarrollos

The Application of Nonlinear Spectral Subtraction Method on Millimeter Wave Conducted Speech Enhancement

A nonlinear multiband spectral subtraction method is investigated in this study to reduce the colored electronic noise in millimeter wave (MMW) radar conducted speech. Because the over-subtraction factor of each Bark frequency band can be adaptively adjusted, the nonuniform effects of colored noise in the spectrum of the MMW radar speech can be taken into account in the enhancement process. Both the results of the time-frequency distribution analysis and perceptual evaluation test suggest that a better whole-frequency noise reduction effect is obtained, and the perceptually annoying musical noise was efficiently reduced, with little distortion to speech information as compared to the other standard speech enhancement algorithm