Carnegie Mellon's Harpy System
Sherry Yu-Ting
Wansu
Janice
Wenjun Meng
Carnegie Mellon's Harpy System
Jump to navigationJump to search
Introduction
The Harpy connected speech recognition system is the attempt to understand two earlier speech recognition systems developed at Carnegie-Mellon University : The Hearsey-1 system and the Dragon system. The two system have slightly different approaches in terms of XXX. The Hearsay 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 xxx. The Hearsay System cannot recognize sentences in unrestricted English and can only recognize (?) simple phrase structure languages.
beam research
Harpy is a result of combing and improving the best features from two speech systems previously developed at Carnegie Mellon University : Hearsay-1 and Dragon. Two feature of the harpy system that led to a successful demonstration are its representation of knowledge and the use of new search techniques. In developing speech recognition systems, it is necessary to devise a means of acquiring and representing the many diverse types of knowledge that characterize speech. We must also develop matching and searching techniques that convert this passive knowledge into an active process for understanding the utterance in the presence of error, noise, and uncertainty. First, some aspects of knowledge representation- the document retrieval tasks when a user speaks to the system, his utterance must conform to the grammar and vocabulary for that task
Harpy When an utterance is input to the computer. Several pre-processing steps are taken to prepare the data for recognition. The utterance is digitalized segmented into acoustic units and analyzed to determine the segmented features and parameters. The goal of recognition tasks is to find an optimal sequence of phones satisfying two criteria: the sequence must represent a legal path through the knowledge network and should consist of phones with high acoustic matches.
Harpy uses a beam search to locate this optimal sequence of phones. Harpy begins the beam search by taking all legal phones from the start of the sentence from the knowledge network and entering them in a recognition free. Next, a path probability is calculated for each candidate. The path with the best probability is determined and remaining candidates are compared with it. Those that fall below a threshold of acceptability are eliminated from further searching. The successors of the surviving candidates are expanded based on the information in the knowledge network.
| Feature | Hearsay System | Dragon System | Harpy System |
|---|---|---|---|
| Model | cooperating parallel process | probabilistic function of a Markov process | |
| Search Strategy | Best-First | all paths in parallel ( search all the possible syntactic
and acoustic paths through the network in parallel to determine optimal path ) |
Beam Research |
| Segmentation | uses it to reduce effective utterance length | X |
- simple intro of the relationship between hearsay-I, Dragon system, and harpy system
- general info about how harpy system works (features, methods
- simply mention the advatages of harpy sytem
Historical Context
- detailed info about hearsay-I and dragon
- 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.
- Hearsay System System Tested: :
| Hearsay System | Dragon System | ||
|---|---|---|---|
| Sources of Knowledge |
|
||
| What Have Been Tested | 144 connected utterances
676 words 5 speakers 4 tasks: Chess, News Retrieval, Medical Diagnosis, Desk Calculator 28-76 word vocabularies |
||
| Performance | % of words spotted and identified correctly
89% with all the sources of knowledge 67% without semantics 44% without syntax and semantics (as of October, 1973) |
Harpy Sytem
- detailed info of the current system
- with a table comparing three systems
Impact
- advantages (improvements on speech recognition tech
Key Innovations
- how the optimization make the improvements
- implications
Future research
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. Cite error: The opening <ref> tag is malformed or has a bad name
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.Cite error: The opening <ref> tag is malformed or has a bad name and a reference comes at the end automatically. Please use this method to cite for Wiki articles only, not for your thesis.
Insert paragraph [1]
- ↑ Lowerre, B., & Reddy, R. (1976). The harpy speech recognition system: performance with large vocabularies. The Journal of the Acoustical Society of America, 60(S1), S10-S11.