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Avances en el procesamiento del lenguaje natural

Julia Hirschberg1, Christopher D Manning2

  • 1Department of Computer Science, Columbia University, New York, NY 10027, USA. julia@cs.columbia.edu.

Science (New York, N.Y.)
|July 18, 2015
PubMed
Resumen
Este resumen es generado por máquina.

El procesamiento del lenguaje natural (PNL) utiliza computadoras para entender y generar lenguaje humano. Las aplicaciones modernas de PNL van desde la traducción y el reconocimiento de voz hasta el análisis de redes sociales y la detección de sentimientos.

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Área de la Ciencia:

  • Ciencias de la computación
  • Inteligencia artificial
  • Lingüística computacional

Sus antecedentes:

  • El procesamiento del lenguaje natural (PNL) implica métodos computacionales para la comprensión y generación del lenguaje.
  • La PNL temprana se centró en el análisis lingüístico y las tecnologías fundamentales como la traducción automática.
  • La investigación actual aprovecha las herramientas de PNL para aplicaciones avanzadas en el mundo real.

Objetivo del estudio:

  • Revisar los avances y los desafíos en curso en el procesamiento del lenguaje natural.
  • Para resaltar la evolución de la PNL desde el análisis básico hasta las aplicaciones sofisticadas.

Principales métodos:

  • Revisión de las técnicas computacionales aplicadas al lenguaje humano.
  • Análisis del desarrollo histórico y el estado actual de las tecnologías de PNL.

Principales resultados:

  • Se han logrado avances significativos en el reconocimiento del habla, la traducción automática y la síntesis del habla.
  • La PNL ahora se usa ampliamente en sistemas de diálogo hablado, motores de traducción y análisis de redes sociales.
  • Las aplicaciones incluyen minería de información financiera y de salud, análisis de sentimientos y emociones.

Conclusiones:

  • La PNL ha demostrado un éxito considerable en varios ámbitos.
  • Los desafíos permanecen en el avance de las capacidades y aplicaciones de PNL.