Optimization Scheme of Joint Noise Suppression and Dereverberation Based on Higher-Order Statistics

APSIPA ASC 2012 : Asia-Pacific Signal and Information Processing Association 2012 Annual Summit and Conference, December 3-6, 2012, Hollywood, California, USA.In this paper, we apply the higher-order statistics parameter to automatically improve the performance of blind speech enhancement. Recently, a method to suppress both diffuse background noise and late reverberation part of speech has been proposed combining blind signal extraction and Wiener filtering. However, this method requires a good strategy for choosing the set of its parameters in order to achieve the optimum result and to control the amount of musical noise, which is a common problem in non-linear signal processing. We present an optimization scheme to control the value of Wiener filter coefficients used in this method, which depends on the amount of musical noise generated, measured by higher-order statistics. The noise reduction rate and cepstral distortion are also evaluated to confirm the effectiveness of this scheme

Noise cancelling in acoustic voice signals with spectral subtraction

The main purpose of study throughout this entire End of Degree Project would be the noise removal within speech signals, focusing on the diverse amount of algorithms using the spectral subtraction method. A Matlab application has been designed and created. The application main goal is to remove any meaningless thing considered as a disturb element when trying to perceive a voice; that is, anything considered as a noise. Noise removal is the basis for any voice processing that the user wants to do later, as speech recognition, save the clean audio, voice analysis, etc. A studio on four algorithms has been executed, in order to perform the spectral subtraction: Boll, Berouti, Lockwood & Boudy, and Multiband. This document presents a theoretical study and its implementation. Moreover, in order to have ready for the user a suitable implementation of an application, an intuitive and simple interface has been designed. This document shows how the different algorithms work in some voices and with various types of noise. A few amounts of noises are ideal, used by its mathematical characteristics, while others, are quite common and presented in daily routine, it is presented as for example, the noise of a bus. To apply the method of spectral subtraction is necessary the implementation of a Vocal Activity Detector, able to recognize in which precise moments of the audio there is voice or not. Two types have been studied and implemented: the first one establishes the meaning of voice according to a threshold which is adequate to this record, while the second one is the combination of Zero Crossing Rate and energy. In the end, once the application is implemented, evaluating its performances was the next process, either in an objective and a subjective form. People stand point was considered and asked, in order to obtain the proper functioning of the application along different types of noise, voice, variables, algorithm, etc.Este Trabajo de Fin de Grado, consiste en el estudio de la eliminación de ruido en voces; en concreto en el estudio de distintos algoritmos para el método de la resta espectral. Se ha creado una aplicación en el programa de cálculo Matlab cuyo uso es la eliminación de todo aquello que nos pueda molestar a la hora de escuchar una voz, es decir, lo que se considera ruido. La eliminación de ruido es la base de cualquier tratamiento de voz que se quiera aplicar posteriormente; desde reconocimiento de voz, el análisis de la misma, la conservación de la grabación limpia. etc. Se ha hecho un estudio de cuatro algoritmos para llevar a cabo esta resta espectral: Boll, Berouti, Lockwood & Boudy y Multibanda. En este documento se encuentra tanto un estudio teórico, así como su implementación. Para la implementación de una aplicación que pueda ser usada por un usuario, se ha diseñado una interfaz fácil e intuitiva de usar, en ésta se muestra cómo funcionan los distintos algoritmos en distintas voces y con distintos tipos de ruido, algunos ideales, usados en las medidas oficiales de ruido por sus concretas características matemáticas, y otros, los de la vida cotidiana como el ruido de un autobús. Para aplicar el método de la resta espectral es necesario la implementación de un Detector de Actividad Vocal (VAD) que reconozca en qué momentos del audio hay voz o no. Se han estudiado e implementado dos: Uno de ellos establece qué es voz según un límite adecuado a esa grabación y el otro es la combinación de la Tasa de Cruces por Cero (ZCR) y la energía. Por último, una vez implementada esta aplicación se ha procedido a evaluar su funcionamiento, tanto de una forma objetiva como subjetiva, a través de la escucha de distintas personas, las cuales dan su opinión, para poder obtener el comportamiento de la aplicación con distintos tipos de ruidos, voces, variables, algoritmos, etc.Ingeniería de Sistemas Audiovisuale