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Nlp

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Andrea Hill
Andrea Hill

While natural language processing has advanced, natural language generation is still in its early stages. Computers cannot yet create unique and grammatical statements in a meaningful way like humans can. The author tested several online translation tools by inputting English text, translating it to and from other languages, and then back to English. The results showed that the translated text was never exactly the same as the original and often had incorrect grammar, showing the limitations of current natural language generation systems.

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The Limitations of Natural Language Processing and Generation Systems Andrea Hill COMP 660
Definitions Natural language processing (NLP) is a subfield of artificial intelligence and linguistics. It studies the problems inherent in the processing and manipulation of natural language, and, natural language understanding devoted to making computers "understand" statements written in human languages. - from Wikipedia: The Free Encyclopedia
Definitions Natural Language Generation (NLG) is the natural language processing task of generating natural language from a machine representation system such as a knowledge base or a logical form. Some people view NLG as the opposite of natural language understanding. - from Wikipedia: The Free Encyclopedia
Definitions Machine translation (MT) is a form of translation where a computer program analyses the text in one language the "source text" and then attempts to produce another, equivalent text in another language the target text without human intervention. - from Wikipedia: The Free Encyclopedia
Hypothesis While dramatic advances have been made in the area of natural language processing, the complimentary process of natural language generation is still in its infancy stage. The creation of unique, grammatical statements remains a human activity that can not yet be performed by computers in a meaningful way.
Experimentation Looked at four online translation websites (translation2.paralink.com, babelfish.altavista.com, systransoft.com, online-translator.com ) Input a source text in English, translated it into a target language of French, Spanish, German or Russian, then back to English Evaluated the services based on how accurate the meaning was retained, as well as the grammaticality of the output
Sample Results English: This is some sample text to see how well these online translation tools work. I will see how well the text is translated to and from the following: French, German and Russian. Here goes! German: Dieses ist etwas Beispieltext, zum wie gut man dieser on-line-bersetzungshilfsmittel zu sehen, arbeitet. Ich sehe, da wie gut der Text nach und von dem folgenden 端bersetzt wird: Franz旦sisch, Deutscher und Russe. Geht hier! And back: This is something example text, to as to be seen well one these on-line translation aids, works. I see that like well the text to and by the following one translates: French, Germans and Russian. Goes here! - babelfish.altavista.com
Sample Results English: This is some sample text to see how well these online translation tools work. I will see how well the text is translated to and from the following: French, German and Russian. Here goes! Russian: 亅仂 弍亟亠 仆亠从仂仂亶 亠从 仂弍舒亰舒 亟仍 仂亞仂 仂弍 于亳亟亠 how well 亳 online 仗仂仂弍亳 亟仍 仗亠亠于仂亟舒 舒弍仂舒. 亊 于亳亢 how well 亠从 仗亠亠于亠亟亠仆 to and from following: 个舒仆亰, 仆亠仄亠 亳 从亳亶. 亟亠 亳亟亠! And back.. This wakes a certain text of model so that he would see how well these online benefits for the transfer it would work. 4 to uvizhu how well text is translated to and from following: Franchuz, German and Russian. Here it goes! -Systransoft.com
Interpretation of Results Translations back to source language were never exactly the same as the original text, but this is common with human-performed translations The grammar of the final results was often incorrect
Conclusion NLG systems are not yet robust enough to function without human intervention. Even if we can build powerful systems, they will require ongoing modifications as language develops Computers are great, but we as humans are irreplaceable!

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Nlp

  • 1. The Limitations of Natural Language Processing and Generation Systems Andrea Hill COMP 660
  • 2. Definitions Natural language processing (NLP) is a subfield of artificial intelligence and linguistics. It studies the problems inherent in the processing and manipulation of natural language, and, natural language understanding devoted to making computers "understand" statements written in human languages. - from Wikipedia: The Free Encyclopedia
  • 3. Definitions Natural Language Generation (NLG) is the natural language processing task of generating natural language from a machine representation system such as a knowledge base or a logical form. Some people view NLG as the opposite of natural language understanding. - from Wikipedia: The Free Encyclopedia
  • 4. Definitions Machine translation (MT) is a form of translation where a computer program analyses the text in one language the "source text" and then attempts to produce another, equivalent text in another language the target text without human intervention. - from Wikipedia: The Free Encyclopedia
  • 5. Hypothesis While dramatic advances have been made in the area of natural language processing, the complimentary process of natural language generation is still in its infancy stage. The creation of unique, grammatical statements remains a human activity that can not yet be performed by computers in a meaningful way.
  • 6. Experimentation Looked at four online translation websites (translation2.paralink.com, babelfish.altavista.com, systransoft.com, online-translator.com ) Input a source text in English, translated it into a target language of French, Spanish, German or Russian, then back to English Evaluated the services based on how accurate the meaning was retained, as well as the grammaticality of the output
  • 7. Sample Results English: This is some sample text to see how well these online translation tools work. I will see how well the text is translated to and from the following: French, German and Russian. Here goes! German: Dieses ist etwas Beispieltext, zum wie gut man dieser on-line-bersetzungshilfsmittel zu sehen, arbeitet. Ich sehe, da wie gut der Text nach und von dem folgenden 端bersetzt wird: Franz旦sisch, Deutscher und Russe. Geht hier! And back: This is something example text, to as to be seen well one these on-line translation aids, works. I see that like well the text to and by the following one translates: French, Germans and Russian. Goes here! - babelfish.altavista.com
  • 8. Sample Results English: This is some sample text to see how well these online translation tools work. I will see how well the text is translated to and from the following: French, German and Russian. Here goes! Russian: 亅仂 弍亟亠 仆亠从仂仂亶 亠从 仂弍舒亰舒 亟仍 仂亞仂 仂弍 于亳亟亠 how well 亳 online 仗仂仂弍亳 亟仍 仗亠亠于仂亟舒 舒弍仂舒. 亊 于亳亢 how well 亠从 仗亠亠于亠亟亠仆 to and from following: 个舒仆亰, 仆亠仄亠 亳 从亳亶. 亟亠 亳亟亠! And back.. This wakes a certain text of model so that he would see how well these online benefits for the transfer it would work. 4 to uvizhu how well text is translated to and from following: Franchuz, German and Russian. Here it goes! -Systransoft.com
  • 9. Interpretation of Results Translations back to source language were never exactly the same as the original text, but this is common with human-performed translations The grammar of the final results was often incorrect
  • 10. Conclusion NLG systems are not yet robust enough to function without human intervention. Even if we can build powerful systems, they will require ongoing modifications as language develops Computers are great, but we as humans are irreplaceable!