DARPA Speech Understanding Research

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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 at the time, 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. Thus, the goals that DARPA set for the project significantly exceeded the state of the art solutions.

Project Progess

The research groups were established at Carnegie-Melon, SRI, MIT's Lincoln Laboratory, Systems Development Corporation (SDC) and Bolt, Beranek and Newman (BNN). CMU researches demonstrated two systems, HARPY and HEARSAY-II, and BNN developed Hear What I mean (HWIM).

One particular contribution from the Harpy system was the concept of doing a graph search, where the speech recognition language was represented as a connected network derived from lexical representations of words, with syntactical production rules and word boundary rules. In the proposed Harpy system, the input speech, after going through a parametric analysis, was segmented and the segmented parametric sequence of speech was then subjected to phone template matching using the Itakura distance [22]. The graph search, based on a beam search algorithm, compiled, hypothesized, pruned, and then verified the recognized sequence of words (or sounds) that satisfied the knowledge constraints with the highest matching score (smallest distance to the reference patterns). The Harpy system was perhaps the first to take advantage of a finite state network to reduce computation and efficiently determine the closest matching string.

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