Repositorio Institucional
Repositorio Institucional
CONICET Digital
  • Inicio
  • EXPLORAR
    • AUTORES
    • DISCIPLINAS
    • COMUNIDADES
  • Estadísticas
  • Novedades
    • Noticias
    • Boletines
  • Ayuda
    • General
    • Datos de investigación
  • Acerca de
    • CONICET Digital
    • Equipo
    • Red Federal
  • Contacto
JavaScript is disabled for your browser. Some features of this site may not work without it.
  • INFORMACIÓN GENERAL
  • RESUMEN
  • ESTADISTICAS
 
Artículo

Automatic classification of Furnariidae species from the Paranaense Littoral region using speech-related features and machine learning

Albornoz, Enrique MarceloIcon ; Vignolo, Leandro DanielIcon ; Sarquis, Juan AndrésIcon ; Leon, Evelina JesicaIcon
Fecha de publicación: 03/2017
Editorial: Elsevier Science
Revista: Ecological Informatics
ISSN: 1574-9541
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Ciencias de la Computación

Resumen

Over the last years, researchers have addressed the automatic classification of calling bird species. This is important for achieving more exhaustive environmental monitoring and for managing natural resources. Vocalisations help to identify new species, their natural history and macro-systematic relations, while computer systems allow the bird recognition process to be sped up and improved. In this study, an approach that uses state-of-the-art features designed for speech and speaker state recognition is presented. A method for voice activity detection was employed previous to feature extraction. Our analysis includes several classification techniques (multilayer perceptrons, support vector machines and random forest) and compares their performance using different configurations to define the best classification method. The experimental results were validated in a cross-validation scheme, using 25 species of the family Furnariidae that inhabit the Paranaense Littoral region of Argentina (South America). The results show that a high classification rate, close to 90%, is obtained for this family in this Furnariidae group using the proposed features and classifiers.
Palabras clave: BIRD SOUND CLASSIFICATION , COMPUTATIONAL BIOACOUSTICS , FURNARIIDAE , MACHINE LEARNING , SPEECH-RELATED FEATURES
Ver el registro completo
 
Archivos asociados
Thumbnail
 
Tamaño: 2.073Mb
Formato: PDF
.
Descargar
Licencia
info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/47572
URL: http://www.sciencedirect.com/science/article/pii/S1574954117300286
DOI: https://doi.org/10.1016/j.ecoinf.2017.01.004
Colecciones
Articulos(SINC(I))
Articulos de INST. DE INVESTIGACION EN SEÑALES, SISTEMAS E INTELIGENCIA COMPUTACIONAL
Citación
Albornoz, Enrique Marcelo; Vignolo, Leandro Daniel; Sarquis, Juan Andrés; Leon, Evelina Jesica; Automatic classification of Furnariidae species from the Paranaense Littoral region using speech-related features and machine learning; Elsevier Science; Ecological Informatics; 38; 3-2017; 39-49
Compartir
Altmétricas
 

Enviar por e-mail
Separar cada destinatario (hasta 5) con punto y coma.
  • Facebook
  • X Conicet Digital
  • Instagram
  • YouTube
  • Sound Cloud
  • LinkedIn

Los contenidos del CONICET están licenciados bajo Creative Commons Reconocimiento 2.5 Argentina License

https://www.conicet.gov.ar/ - CONICET

Inicio

Explorar

  • Autores
  • Disciplinas
  • Comunidades

Estadísticas

Novedades

  • Noticias
  • Boletines

Ayuda

Acerca de

  • CONICET Digital
  • Equipo
  • Red Federal

Contacto

Godoy Cruz 2290 (C1425FQB) CABA – República Argentina – Tel: +5411 4899-5400 repositorio@conicet.gov.ar
TÉRMINOS Y CONDICIONES