DARPA Speech Understanding Research: Difference between revisions

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== Historical Context ==
== Historical Context ==
There had been partially successful attempts to understand discrete speech (see, for example, Bell's [[Bell Labs' Auditory Model|Audrey]]) but no system to understand speech that is continious existed at the time<ref>Funding a Revolution: Government Support for Computing Research. (1999). Украина: National Academies Press.</ref>. Moreover, previous methods dealt with vocabularies no larger than 200 words (e.g., IBM's 16-word "[[IBM Shoebox|Shoebox]]"), while DARPA's SUR aimed at a vocabulary with at least one thousand words.
There had been partially successful attempts to understand discrete speech (see, for example, Bell's [[Bell Labs' Auditory Model|Audrey]]) but there were practically no systems to understand speech that is continious, except for the Raj Reddy's recognition system used for issuing chess commands<ref>Funding a Revolution: Government Support for Computing Research. (1999). Украина: National Academies Press.</ref>. Moreover, previous methods dealt with vocabularies no larger than 200 words (e.g., IBM's 16-word "[[IBM Shoebox|Shoebox]]"), while DARPA's SUR aimed at a vocabulary with at least one thousand words.
== Project Progess ==
== Project Progess ==
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Revision as of 22:15, 15 September 2023

Introduction

DARPA stands for Defense Advanced Research Projects Agency, a research agency of the United States Department of Defense responsible for the development of emerging technologies for use by the military. As the DARPA's then-director George Heilemeir stated, "Get computers to read Morse code in the presence of other code and noise, get computers to identify/detect key words in a stream of speech, [...] make a real contribution to command and control, and; do a good thing in sonar"[1]. Thus, the main reason why it was the US Ministry of Defense who would fund such a project is that it could serve the navy's purposes.

Considering that the project was to be used for military purposes, a number of requirements were put forward for it, especially relevant for military purposes. For example, the system had to be able to recognize several speakers at once, and also have no delay in recognition of speech. Thus, five main objectives of the research were established:

Accepting connected speech
From many cooperative speakers
Accepting 1000 words
Yielding only <10% semantic errors
Real-time understanding

This is the reason why it is understanding in the first place, and not recognition: to attain successful understanding what was said or what was intented to be said rathern than simple recognizing some words taken out of context.

Historical Context

There had been partially successful attempts to understand discrete speech (see, for example, Bell's Audrey) but there were practically no systems to understand speech that is continious, except for the Raj Reddy's recognition system used for issuing chess commands[2]. Moreover, previous methods dealt with vocabularies no larger than 200 words (e.g., IBM's 16-word "Shoebox"), while DARPA's SUR aimed at a vocabulary with at least one thousand words.

Project Progess

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Impact

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Future research

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References

To insert a reference, type <ref> and paste the source your exported from Zotero (or whatever reference manager you're using) in the pop up box which appears. Make sure links in citations are clickable using proper formatting. Once you do this, a footnote will appear.[3] and a reference comes at the end automatically. Please use this method to cite for Wiki articles only, not for your thesis.

  1. Gaon, A. (2021). The Future of Copyright in the Age of Artificial Intelligence. Великобритания: Edward Elgar Publishing.
  2. Funding a Revolution: Government Support for Computing Research. (1999). Украина: National Academies Press.
  3. Glantz, Richard "SHOEBOX: a personal file handling system for textual data." In Proceedings of the November 17-19, 1970, Fall Joint Computer Conference 1970. 535-545. [1]

Group members

  • Igor Marchenko
  • Wangyiyao Zhou
  • Yanpei Ouyang
  • Youyang Cai
  • Yi Lei