iPEEH: Improving pitch estimation by enhancing harmonics

Wu, Kebin; Zhang, David; Lu, Guangming

doi:10.1016/j.eswa.2016.08.018

“…Los resultados encontrados se muestran en la figura 6, en la que se observa que el análisis espectral es el más estudiado. Los artículos 1 y 9 buscan mejorar la periodicidad de la señal para garantizar la correcta detección, según [41] y [49], mientras que otras propuestas utilizan métodos que implican un mayor procesamiento, como el artículo 5, según [45], en el que se utiliza un filtro de partículas.…”

Section: Pitch Detection Methods Based On Morphological Filtering and Hhtunclassified

“…1. Improving pitch estimation by enhancing harmonics [41] Se propone un método de detección de la frecuencia fundamental de la voz en el dominio de la frecuencia. La señal de voz pasa por una etapa de preprocesamiento cuando se mejora la diferenciación de los armónicos, lo que da como resultado un mejor desempeño en presencia del ruido.…”

Section: Métodos De Detección De La Frecuencia Fundamental De La Vozunclassified

Técnicas de detección de la frecuencia fundamental de la voz en entornos reales

Zambrano

¹

,

Romero

²

,

Viáfara

³

et al. 2017

ing. Solidar

0

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Introducción: este artículo de revisión se desarrolló como parte de un trabajo de maestría de la Universidad del Cauca en el 2017. Buscó encontrar los métodos de detección de la frecuencia fundamental de la voz más propicios para implementar en entornos reales como parte de una solución para mejorar la comunicación de las personas con discapacidad auditiva e incluirlas en la sociedad, ya que la mayoría de las propuestas solo plantean mejorar el canal de comunicación en el que la persona con discapacidad auditiva es el transmisor. Metodología: se realizó una revisión actualizada de la literatura, por lo que se basó principalmente en artículos científicos publicados en los últimos cinco años. Para la inclusión de artículos se hizo un mapeo sistemático sobre los diferentes métodos de detección de la frecuencia fundamental de la voz. Resultados: los fenómenos contemplados por los diferentes algoritmos para definir el entorno van desde el ruido y la interferencia hasta la reverberación; el desempeño del algoritmo depende de la calidad del audio grabado, lo que se ve en las variaciones obtenidas que dependen de la base de datos utilizada; se pueden detectar hasta dos frecuencias fundamentales diferentes. Conclusiones: se han implementado novedosos métodos para hacer más eficiente la detección de la frecuencia fundamental de la voz; sin embargo, aún queda mucho trabajo por hacer en esta área.

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“…Pitch measurements are prone to errors and several attempts to collect valid and reliable values were made (Vogel et al, 2009;Wu et al, 2016;Yang, 2009). Generally, f0 values may vary according to software configuration, signal-to-noise ratio, acquisition environment, and sampling rate (see Vogel et al, 2009 for details).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, to attain valid pitch values, the pitch range should be set appropriately: if the pitch floor or ceiling were too high or too low, the chance of neglecting valid pitch values would increase. Wu et al (2016) proposed a method to improve pitch estimation by enhancing harmonics. Their method is to regenerate harmonics from noisy signals by multiplying existing harmonics.…”

Section: Introductionmentioning

confidence: 99%

Pitch trajectories of English vowels produced by American men, women, and children

Yang¹

2018

Phonetics Speech Sci.

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Pitch trajectories reflect a continuous variation of vocal fold movements over time. This study examined the pitch trajectories of English vowels produced by 139 American English speakers, statistically analyzing their trajectories using the Generalized Additive Mixed Models (GAMMs). First, Praat was used to read the sound data of Hillenbrand et al. (1995). A pitch analysis script was then prepared, and six pitch values at the corresponding time points within each vowel segment were collected and checked. The results showed that the group of men produced the lowest pitch trajectories, followed by the groups of women, boys, then girls. The density line showed a bimodal distribution. The pitch values at the six corresponding time points formed a single dip, which changed gradually across the vowel segment from 204 to 193 to 196 Hz. The normality tests performed on the pitch data rejected the null hypothesis. Nonparametric tests were therefore conducted to discover the significant differences in the values among the four groups. The GAMMs, which analyzed all the pitch data, produced significant results among the pitch values at the six corresponding time points but not between the two groups of boys and girls. The GAMMs also revealed that the two groups were significantly different only at the first and second time points. Accordingly, the methodology of this study and its findings may be applicable to future studies comparing curvilinear data sets elicited by experimental conditions. Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

show abstract

“…Pitch measurements are prone to errors and several attempts to collect valid and reliable values were made (Vogel et al, 2009;Wu et al, 2016;Yang, 2009). Generally, f0 values may vary according to software configuration, signal-to-noise ratio, acquisition environment, and sampling rate (see Vogel et al, 2009 for details).…”

Section: Introductionmentioning

confidence: 99%

Pitch trajectories of English vowels produced by American men, women, and children

Yang¹

2018

Phonetics Speech Sci.

0

View full text Add to dashboard Cite

Pitch trajectories reflect a continuous variation of vocal fold movements over time. This study examined the pitch trajectories of English vowels produced by 139 American English speakers, statistically analyzing their trajectories using the Generalized Additive Mixed Models (GAMMs). First, Praat was used to read the sound data of Hillenbrand et al. (1995). A pitch analysis script was then prepared, and six pitch values at the corresponding time points within each vowel segment were collected and checked. The results showed that the group of men produced the lowest pitch trajectories, followed by the groups of women, boys, then girls. The density line showed a bimodal distribution. The pitch values at the six corresponding time points formed a single dip, which changed gradually across the vowel segment from 204 to 193 to 196 Hz. The normality tests performed on the pitch data rejected the null hypothesis. Nonparametric tests were therefore conducted to discover the significant differences in the values among the four groups. The GAMMs, which analyzed all the pitch data, produced significant results among the pitch values at the six corresponding time points but not between the two groups of boys and girls. The GAMMs also revealed that the two groups were significantly different only at the first and second time points. Accordingly, the methodology of this study and its findings may be applicable to future studies comparing curvilinear data sets elicited by experimental conditions.

show abstract

iPEEH: Improving pitch estimation by enhancing harmonics

Cited by 10 publications

References 36 publications

Técnicas de detección de la frecuencia fundamental de la voz en entornos reales

Técnicas de detección de la frecuencia fundamental de la voz en entornos reales

Pitch trajectories of English vowels produced by American men, women, and children

Pitch trajectories of English vowels produced by American men, women, and children

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