Editing Carnegie Mellon's Harpy System (section)

== Historical Context ==
'''Before 1970s''', the speech recognition systems available in the world could only understand '''16 words''' spoken in English. With the goal of ending up with a machine capable of understanding a minimum of 1,000 words, speech recognition technology made major strides '''in the 1970s''', thanks to interest and funding from the U.S. Department of Defense. The DoD’s [https://wiki.voice-technology.nl/index.php/DARPA_Speech_Understanding_Research DARPA Speech Understanding Research]<ref>''DARPA Speech Understanding Research''. (2023). [[DARPA Speech Understanding Research|https://wiki.voice-technology.nl/index.php/DARPA_Speech_Understanding_Research]]</ref> (SUR) program, '''from 1971 to 1976''', funds five years of speech recognition research leading to the creation of the Harpy by Carnegie Mellon, a machine capable of understanding '''1,011 words''', approximately the vocabulary of an average three-year-old<ref>Pinola, M. (2011). ''Speech Recognition Through the Decades: How We Ended Up With Siri.'' <nowiki>https://www.pcworld.com/article/477914/speech_recognition_through_the_decades_how_we_ended_up_with_siri.html</nowiki></ref>.

The Harpy connected speech recognition system is the result of an attempt to understand the relative importance of various design choices of two earlier speech recognition systems developed at Carnegie-Mellon University: the Hearsay-I system and the Dragon system. Systematic performance analysis of various design choices of these two systems resulted in the Harpy system. 

=== Hearsay-I System ===
*'''The Hearsay-I System''' must use all these sources of knowledge effectively in the Hearsay System, this is achieved by representing knowledge as as a set of '''cooperating parallel process'''. The Hearsay System also use the source of knowledge ('''acoustics-phonetics, prosody, lexicon, syntax, semantics and pragmatics''') to '''generate hypothesis''' about what words might appear. The Hearsay System is incrementally trying to match words to the un-analyzed portion of the utterance 
*If the resulting word matches are not optimal, the system '''backs up and tries a different path'''. The technique was known as probabilistic tree. The Hearsay System '''cannot''' recognize sentences in unrestricted English and can only recognize simple phrase structure languages.
*To be acceptable as an input medium, the system must not only perform with high accuracy, but it must also minimize the combinatorial explosion so as to respond as fast as a human would in a similar situation.

=== Dragon System<ref name=":0">Lowerre, B. T. (1976). ''The HARPY Speech Recognition System''. Department of Computer Science, Carnegie-Mellon University.</ref> ===

*'''The Dragon system''' is interesting for its simplicity of design, mathematical tractability and high accuracy performance, which can achieve 100% accuracy on a set of speech data using only '''syntactic and acoustic-phonetic knowledge''';
*It achieves recognition by updating state probabilities of a '''Markov network'''. All possible paths are searched in parallel by a '''dynamic programming scheme''' and lead through states representing all syntactic and phonetic pronunciations;
*The most significant feature of the system is that it '''contains no coded heuristics''' except for the '''acoustic probability matching routine'''. It shows that there is a search algorithm which guarantees a recognition and in a deterministic amount of time.

{| class="wikitable"
|+
!
!Hearsay-I System
!Dragon System
|-
|Model 
|cooperating parallel process
|probabilistic function of Markov Process 
|-
|knowledge representation
|Procedures 
|Markov Networks
|-
|Unit of Speech 
Signal Representation  
|segmentation 
|10 milli-second sample 
|-
|search strategy 
|best-first 
|all paths in parallel
|-
|search time 
|8-50 times real-time
|45-200 times real-time
|-
|What Have Been Tested
|144 connected utterances 
676 words  

5 speakers 
 
4 tasks: Chess, News Retrieval, Medical Diagnosis, Desk Calculator  

28-76 word vocabularies 
|102 utterances
564 words<ref name=":1">Lowerre, B. T. (1974). Comparison of Two Speech Understanding Systems. ''The Journal of the Acoustical Society of America'', ''56, S27''. <nowiki>https://pubs.aip.org/asa/jasa/article/56/S1/S27/740227/Comparison-of-two-speech-understanding-systems</nowiki></ref>
|-
|Performance
|<u>Percentage of words spotted and identified correctly</u> <ref>Reddy, R. (2013). ''CMU Hearsay 1973 (Short Version)''. Retrieved September 17, 2023, from <nowiki>https://www.youtube.com/watch?v=c70QlwttnVg</nowiki>.</ref> 
89% with all the sources of knowledge 

67% without semantics 

44% without syntax and semantics 

(as of October, 1973)
|85% of the words identified correctly<ref name=":1" />
|-
|Approaches 
|acoustics-phonetics, prosody, lexicon, syntax, semantics and pragmatics
|Treats speech recognition as a mathematical computation problem
rather than as an artificial intelligence problem. 
|}