Techniques for detecting voice fundamental frequency in real environments

Introduction: This review article was prepared as part of a graduate thesis at Universidad del Cauca in 2017. It sought to find the most appropriate methods for detecting voice fundamental frequency to be implemented in real environments. This is part of a solution to improve the communication of pe...

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Autores:
Silva Zambrano, María Manuela
Romo Romero, Harold Armando
Ramírez Viáfara, Jesús Mauricio
Galvis Zambrano, Diana María
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Universidad Cooperativa de Colombia
Repositorio:
Repositorio UCC
Idioma:
spa
OAI Identifier:
oai:repository.ucc.edu.co:20.500.12494/9422
Acceso en línea:
https://revistas.ucc.edu.co/index.php/in/article/view/2006
https://hdl.handle.net/20.500.12494/9422
Palabra clave:
Rights
openAccess
License
Copyright (c) 2017 Journal of Engineering and Education
Description
Summary:Introduction: This review article was prepared as part of a graduate thesis at Universidad del Cauca in 2017. It sought to find the most appropriate methods for detecting voice fundamental frequency to be implemented in real environments. This is part of a solution to improve the communication of people with hearing disabilities and include them in society, since most of the proposals only aim to improve the communication channel in which the hearing-impaired individual is the transmitter. Methodology: An updated review of the literature was carried out, based mainly on scientific articles published in the last five years.  For the inclusion of articles, a systematic mapping was performed on the different methods for detecting voice fundamental frequency. Results: the phenomena considered by the various algorithms to define the environment range from noise and interference to reverberation; the performance of the algorithm depends on the quality of the recorded audio, which is observed in the variations obtained which depend on the database used; up to two different fundamental frequencies can be detected. Conclusions: Novel methods have been implemented to make the detection of voice fundamental frequency more efficient; however, there is still much work to be done in this area.