Analisis de integrada wavelet de señales no audibles
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Universidad Distrital Francisco José de Caldas. Colombia
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El análisis de señales no audibles ha ganado una importancia significativa debido a sus muchos campos de aplicación, entre ellos, la síntesis del habla para personas con discapacidades del habla. Este análisis puede usarse para obtener información del aparato vocal sin la necesidad de hablar para producir una expresión fonética. Se propone el análisis de una transformación Wavelet de palabras en español grabadas a través de un micrófono de murmullo no audible para lograr un sistema integrado de reconocimiento de voz silenciosa del idioma español. Se usa un micrófono de soplo no audible como sensor de habla no vocal. La codificación de los datos de entrada se realiza a través de una transformación Wavelet utilizando una función Daubechies de cuarto orden. El sistema de adquisición, procesamiento y transmisión se aplica a través de una placa de evaluación STM32F4-Discovery. El vocabulario utilizado consiste en palabras de comando destinadas a controlar robots móviles o interfaces hombre-máquina. Se logró la transformación Wavelet de cuatro palabras en español, cada una de ellas con cinco muestras independientes. Se realizó un análisis de los datos resultantes y se distinguieron características como promedio, picos y frecuencia. El procesamiento de las señales se realiza con éxito y se propone un trabajo adicional en la detección de la actividad del habla y clasificadores de características.
The analysis of non-audible signals has gain a significant importance due to its many fields of application, among them, speech synthesis for people with speech disabilities. This analysis can be used to acquire information from the vocal apparatus without the need of speaking in order to produce a phonetic expression. The analysis of a Wavelet transformation of Spanish words recorded through a non-audible murmur microphone in order to achieve an embedded silent speech recognition system of Spanish language is proposed. A non-audible murmur microphone is used as sensor of non-vocal speech. Coding of the input data is done through a Wavelet transform using a fourth-order Daubechies function. The acquisition, processing and transmission system is applied through a STM32F4-Discovery evaluation board. The vocabulary utilized consists of command words aimed to control mobile robots or human-machine interfaces. The Wavelet transformation of four Spanish words, each of them having five independent samples, was accomplished. An analysis of the resulting data was performed, and features as average, peaks and frequency were distinguished. The processing of the signals is performed successfully and further work in speech activity detection and features classifiers is proposed.
The analysis of non-audible signals has gain a significant importance due to its many fields of application, among them, speech synthesis for people with speech disabilities. This analysis can be used to acquire information from the vocal apparatus without the need of speaking in order to produce a phonetic expression. The analysis of a Wavelet transformation of Spanish words recorded through a non-audible murmur microphone in order to achieve an embedded silent speech recognition system of Spanish language is proposed. A non-audible murmur microphone is used as sensor of non-vocal speech. Coding of the input data is done through a Wavelet transform using a fourth-order Daubechies function. The acquisition, processing and transmission system is applied through a STM32F4-Discovery evaluation board. The vocabulary utilized consists of command words aimed to control mobile robots or human-machine interfaces. The Wavelet transformation of four Spanish words, each of them having five independent samples, was accomplished. An analysis of the resulting data was performed, and features as average, peaks and frequency were distinguished. The processing of the signals is performed successfully and further work in speech activity detection and features classifiers is proposed.
Palabras clave
Communication Aids for Disabled, Esophageal, Phonetics, Speech, Wavelet Analysis., Communication Aids for Disabled, Esophageal, Phonetics, Speech, Wavelet Analysis.