https://apps.dtic.mil/sti/pdfs/ADA157550.pdf

The TRACE model of speech perception.

The reviewing of object files: object-specific integration of information.

Preface Similarity and analogical reasoning: a synthesis Stella Vosniadou and Andrew Ortony Part I. Similarity and the Structure of Concepts: 1. Similarity, typicality, and categorization Lance J. Rips 2. Similarity and decision making Edward E. Smith and Daniel N. Osherson 3. Intraconcept similarity and its implications for interconcept similarity Lawrence W. Barsalou 4. Two-tiered concept meaning, inferential matching, and conceptual cohesiveness Ryszard S. Michalski 5. From global similarities to kinds of similarities: the construction of dimensions in development Linda B. Smith 6. Comments on Part I. Psychological essentialism Douglas Medin and Andrew Ortony Part II. Analogical Reasoning: 7. The mechanisms of analogical learning Dedre Genter 8. A computational model of analogical problem solving Keith J. Holyoak and Paul R. Thagard 9. Use of analogy in production system architecture John R. Anderson and Ross Thompson 10. Toward a microstructural account of human reasoning David E. Rumelhart 11. Analogy and the exercise of creativity Philip N. Johnson-Laird 12. Comments on Part II. Levels of description in information-processing theories of analogy Stephen E. Palmer 13. Comments on Part II. The role of explanation in analogy or, the curse of an alluring name Gerald Dejong Part III. Similarity and Analogy in Development, Learning and Instruction: 14. Analogical learning and transfer: what develops? Ann L. Brown 15. Analogical reasoning as a mechanism in knowledge acquisition: a developmental perspective Stella Vosniadou 16. Remindings in learning and instruction Brian H. Ross 17. New approaches to instruction: because wisdom can't be told John D. Bransford, Jeffery J. Franks, Nancy J. Vye and Robert Sherwood 18. Multiple analogies for complex concepts: antidotes for analogy-induced misconception in advanced knowledge acquisition Rand J. Spiro, Paul J. Feltovich, Richard L. Coulson and Daniel K. Anderson 19. Comments on Part III. The activation and acquisition of knowledge William F. Brewer Afterword Allan Collins and Mark Burstein Name index Subject index.

http://old.nbu.bg/cogs/personal/kokinov/COG501/SimilarityandAnalogicalReasoning.pdf

Similarity and analogical reasoning

The Hearsay-II system, developed during the DARPA-sponsored five-year speech-understanding research program, represents both a specific solution to the speech-understanding problem and a general framework for coordinating independent processes to achieve cooperative problem-solving behavior. As a computational problem, speech understanding reflects a large number of intrinsically interesting issues. Spoken sounds are achieved by a long chain of successive transformations, from intentions, through semantic and syntactic structuring, to the eventually resulting audible acoustic waves. As a consequence, interpreting speech means effectively inverting these transformations to recover the speaker's intention from the sound. At each step in the interpretive process, ambiguity and uncertainty arise.

The Hearsay-II problem-solving framework reconstructs an intention from hypothetical interpretations formulated at various levels of abstraction. In addition, it allocates limited processing resources first to the most promising incremental actions. The final configuration of the Hearsay-II system comprises problem-solving components to generate and evaluate speech hypotheses, and a focus-of-control mechanism to identify potential actions of greatest value. Many of these specific procedures reveal novel approaches to speech problems. Most important, the system successfully integrates and coordinates all of these independent activities to resolve uncertainty and control combinatorics. Several adaptations of the Hearsay-II framework have already been undertaken in other problem domains, and it is anticipated that this trend will continue; many future systems necessarily will integrate diverse sources of knowledge to solve complex problems cooperatively.

Discussed in this paper are the characteristics of the speech problem in particular, the special kinds of problem-solving uncertainty in that domain, the structure of the Hearsay-II system developed to cope with that uncertainty, and the relationship between Hearsay-II's structure and those of other speech-understanding systems. The paper is intended for the general computer science audience and presupposes no speech or artificial intelligence background.

/pdf/the-hearsay-ii-speech-understanding-system-integrating-4upd3ocgip.pdf

The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty

Most artificial intelligence research investigates intelligent behavior for a single agent--solving problems heuristically, understanding natural language, and so on. Distributed Artificial Intelligence (DAI) is concerned with coordinated intelligent behavior: intelligent agents coordinating their knowledge, skills, and plans to act or solve problems, working toward a single goal, or toward separate, individual goals that interact. DAI provides intellectual insights about organization, interaction, and problem solving among intelligent agents. This comprehensive collection of articles shows the breadth and depth of DAI research. The selected information is relevant to emerging DAI technologies as well as to practical problems in artificial intelligence, distributed computing systems, and human-computer interaction. 

"Readings in Distributed Artificial Intelligence" proposes a framework for understanding the problems and possibilities of DAI. It divides the study into three realms: the natural systems approach (emulating strategies and representations people use to coordinate their activities), the engineering/science perspective (building automated, coordinated problem solvers for specific applications), and a third, hybrid approach that is useful in analyzing and developing mixed collections of machines and human agents working together. 

The editors introduce the volume with an important survey of the motivations, research, and results of work in DAI. This historical and conceptual overview combines with chapter introductions to guide the reader through this fascinating field. A unique and extensive bibliography is also provided.

Readings in Distributed Artificial Intelligence

This paper describes the structure and operation of the Hearsay speech understanding system by the use of a specific example illustrating the various stages of recognition. The system consists of a set of cooperating independent processes, each representing a source of Knowledge. The knowledge is used either to predict what may appear in a given context or to verify hypotheses resulting from a prediction. The structure of the system is illustrated by considering its Operation in a particular task situation: Voice-Chess. The representation and use of various sources of knowledge are outlined. Preliminary results of the reduction in search resulting from the use of various sources of knowledge are given.

/pdf/the-hearsay-speech-understanding-system-an-example-of-the-4p89nosy1k.pdf

The hearsay speech understanding system: an example of the recognition process

This paper presents a model for machine recognition of connected speech and the details of a specific implementation of the model, the HEARSAY system. The model consists of a small set of cooperating independent parallel processes that are capable of helping in the decoding of a spoken utterance either individually or collectively. The processes use the "hypothesize-and-test" paradigm. The structure of HEARSAY is illustrated by considering its operation in a particular task situation: voice-chess. The task is to recognize a spoken move in a given board position. Procedures for determination of parameters, segmentation, and phonetic descriptions are outlined. The use of semantic, syntactic, lexical, and phonological sources of knowledge in the generation and verification of hypotheses is described. Preliminary results of recognition of some utterances are given.

A model and a system for machine recognition of speech

This talk describes the present state of performance of the HEARSAY system. [For more complete descriptions of the system see D. R. Reddy, L. D. Erman, and R. D. Neely, “A Model and a System for Machine Recognition of Speech,” IEEE Trans. Audio Electroacoust. AU‐21, 229–238 (1973) and D. R. Reddy, L. D. Erman, R. D. Fennell, and R. B. Neely, “The HEARSAY Speech Understanding System : An Example of the Recognition Process,” Proc. 3rd Int. Joint Conf. on Artificial Intelligence (Aug. 1973)]. The system uses task and context‐dependent information to help in the recognition of the utterance; this system consists of a set of cooperating parallel processes, each representing a different source of knowledge (e.g., acoustic‐phonetic, syntactic, semantic). The knowledge is used either to predict what may appear in a given context or to verify an hypothesis resulting from a previous prediction. Performance data of the system on several tasks (e.g., medical diagnosis, news retrieval, chess, and programming) will be presented. For example: The voice‐chess task contains a 31‐word vocabulary with about 5 000 000 possible sentences. One particular set of data contains 19 utterances of three to nine (mean =4.5) words each. Seventy‐nine percent of the utterances are correctly recognized (at about four times real time on a PDP10 computer); removing the semantic source of knowledge (but leaving the syntactic and acoustic‐phonetic) reduces recognition to 42%.

The HEARSAY Speech Understanding System

The JABBERWOCKY is a system that greatly simplifies the transcription of verbal protocols by acting as a “smart” tape recorder which plays exactly a phrase at a time. In addition, it provides timings accurate to a centisecond. The final result is available as a file on a computer system that then may be used for other editing or processing.

/pdf/the-jabberwocky-a-semiautomated-system-for-the-transcription-14qgcy0fgt.pdf

The JABBERWOCKY: A semiautomated system for the transcription of verbal protocols

This paperdescribes thestructure andoperation of theHearsay-"1 speech understanding systembytheuseofaspe- cific exampleillustrating thevarious stages ofrecognition. The systemconsists ofasetofcooperating independent processes, eachrepresenting asourceofknowledge. Theknowledge isused either topredict whatmayappearinagiven context ortoverify hypotheses resulting fromaprediction. Thestructure ofthesys- temisillustrated byconsidering itsoperation ina particular tasksituation: Voice-Chess. Therepresentation anduseotvari- oussources ofknowledge areoutlined. Preliminary results of thereduction insearch realIting fromtheuseofvarious sources ofknowledge aregiven. IndexTerms-Hypothesize-and-test, speech recognition, un- derstanding.

https://ieeexplore.ieee.org/iel5/12/35146/01674624.pdf

Richard B. Neely

Papers

The hearsay speech understanding system: an example of the recognition process

A model and a system for machine recognition of speech

The HEARSAY Speech Understanding System

The JABBERWOCKY: A semiautomated system for the transcription of verbal protocols

TheHearsay- ISpeechUnderstanding System: AnExample oftheRecognition Process