Jared C Bernstein, 761330 Tasso St, Palo Alto, CA 94301

7657220, Feb 2, 2010

May 21, 2004

10/851405

Brent Townshend - Menlo Park CA, US
Jared Bernstein - Palo Alto CA, US

Ordinate Corporation - Menlo Park CA

G09B 11/00

434353, 434362

A method for adaptive scoring of responses to constructed response questions is disclosed. Adaptive scoring may be used to apply evaluator time in such a way that a predetermined reliability level is reached with the least possible use of evaluator time, including adjusting the number of response graded and/or the number of evaluators grading each response. A score may be calculated after grading a subset of a test taker's responses to the constructed response questions. A probability or an error estimate is calculated and compared to a threshold value. Grading may be discontinued based on the comparison. A score may be calculated based on a predetermined number of ratings for the test taker's response to a constructed response. A probability that the score is within a predetermined range of what the score would be if all the responses are graded is calculated. If the probability is less than a threshold value, the number of ratings is increased.

2002014, Oct 10, 2002

Mar 1, 2002

10/087651

Brent Townshend - Menlo Park CA, US
Jared Bernstein - Palo Alto CA, US

Ordinate Corporation - Menlo Park CA

G10L015/26

704/235000

An intelligibility measuring system provides a system and method of evaluating intelligibility of a speaker. Intelligibility may be a function of the speaker's pronunciation of words, material being spoken, context in which words are spoken, and skill of a listener. The speaker repeats items. The items may be words or combination of words. The listener hears the speaker articulating items and a transcription is created to document what the listener heard. A measurement unit determines an error count based on a comparison of the items and the transcription. An intelligibility score is then determined using the error count, difficulty level of the items, and ability of the listener.

2006000, Jan 12, 2006

Jul 6, 2005

11/176834

Brent Townshend - Menlo Park CA, US
Jared Bernstein - Palo Alto CA, US

Ordinate Corporation - Menlo Park CA

G09B 17/00

434178000

A system and method for measuring reading skills is described. An individual whose reading skills are to be evaluated reads aloud from a text. As the person reads aloud from the text, a speech signal is captured. The speech signal is analyzed to provide an estimate of what the individual said and to measure a timing of the words said. The estimate and timing is combined with parameters assigned to each word said to form a measure of the individual's reading skill. The measure of the individual's reading skill is substantially independent of the text.

5870709, Feb 9, 1999

Nov 25, 1996

8/753580

Jared C. Bernstein - Palo Alto CA

Ordinate Corporation - Menlo Park CA

G09B 1904
G01L 506

704275

A computer system with a speech recognition component provides a method and apparatus for instructing and evaluating the proficiency of human users in skills that can be exhibited through speaking. The computer system tracks linguistic, indexical and paralinguistic characteristics of the spoken input of users, and implements games, data access, instructional systems, and tests. The computer system combines characteristics of the spoken input automatically to select appropriate material and present it in a manner suitable for the user. In one embodiment, the computer system measures the response latency and speaking rate of the user and presents its next spoken display at an appropriate speaking rate. In other embodiments, the computer system identifies the gender and native language of the user, and combines that information with the relative accuracy of the linguistic content of the user's utterance to select and display material that may be easier or more challenging for speakers with these characteristics.

5581655, Dec 3, 1996

Jan 22, 1996

8/589432

Michael H. Cohen - East Palo Alto CA
Mitchel Weintraub - Fremont CA
Patti J. Price - Palo Alto CA
Hy Murveit - Redwood City CA
Jared C. Bernstein - Menlo Park CA

SRI International - Menlo Park CA

G10L 506

395 254

An automatic speech recognition methodology, wherein words are modeled as probabilistic networks of allophones, collects nodes in the probabilistic network into equivalence classes when those nodes have the same allophonic choices governed by the same phonological rules. The allophonic choices allow for representation of dialectic pronunciation variations between different speakers. Training data is shared among nodes in an equivalence class so that accurate pronunciation probabilities may be determined even for words for which there is only a limited amount of training data. A method is used to determine probabilities for each of a multitude of pronunciation models for each word in the vocabulary, based on automatic extraction of linguistic knowledge from sets of phonological rules, in order to robustly and accurately model dialectal variation.

6157913, Dec 5, 2000

Nov 2, 1998

9/184804

Jared C. Bernstein - Palo Alto CA

G10L 1522
G09B 702

704275

Linguistic and/or extra-linguistic information is extracted from speech signals to provide measures that may then be compared to expected norms, individual baselines or other nominal or numeric criteria (according to particular psychomotor, perceptual, cognitive or emotional constructs) that are required for satisfactory performance of particular tasks, or that indicate a user's psychological or physical state. The user produces the speech signals in the context of a constrained voice-interactive dialog that utilizes prompts chosen such that the expected range of responses will exhibit low linguistic entropy. For example, the prompts may be interpreted by the user as requests for information, requests to read or repeat or paraphrase a word, sentence, or larger linguistic unit, requests to draw an inference, requests to complete, or identify elements in graphic or verbal aggregates (e. g. , pictures or discourses), as examples to imitate, or any similar graphical or verbal presentation that conventionally serves as a prompt to speak. The display is presented though a device either integral or peripheral to a computer system, such as a local or remote video display terminal or telephone.

5634086, May 27, 1997

Sep 18, 1995

8/529376

Dimitry Rtischev - Menlo Park CA
Jared C. Bernstein - Palo Alto CA
George T. Chen - Menlo Park CA
John W. Butzberger - Foster City CA

SRI International - Menlo Park CA

G10L 300
G10L 506
G10L 900

395 279

Spoken-language instruction method and apparatus employ context-based speech recognition for instruction and evaluation, particularly language instruction and language fluency evaluation. A system can administer a lesson, and particularly a language lesson, and evaluate performance in a natural interactive manner while tolerating strong foreign accents, and produce as an output a reading quality score. A finite state grammar set corresponding to the range of word sequence patterns in the lesson is employed as a constraint on a hidden Markov model (HMM) search apparatus in an HMM speech recognizer which includes a set of hidden Markov models of target-language narrations produced by native speakers of the target language. The invention is preferably based on use of a linguistic context-sensitive speech recognizer. The invention includes a system with an interactive decision mechanism which employs at least three levels of error tolerance to simulate a natural level of patience in human-based interactive instruction.

5268990, Dec 7, 1993

Jan 31, 1991

7/648097

Michael H. Cohen - East Palo Alto CA
Mitchel Weintraub - Fremont CA
Patti J. Price - Palo Alto CA
Hy Murveit - Redwood City CA
Jared C. Bernstein - Menlo Park CA

SRI International - Menlo Park CA

G10L 300
G10L 900

395 2

An automatic speech recognition methodology takes advantage of linguistic constraints wherein words are modeled as probabilistic networks of phonetic segments (herein phones), and each phone is represented as a context-independent hidden Markov phone model mixed with a number of context-dependent phone models. Recognition is based on use of methods to design phonological rule sets based on measures of coverage and overgeneration of pronunciations which achieves high coverage of pronunciations with compact representations. Further, a method estimates probabilities of the different possible pronunciations of words. A further method models cross-word coarticulatory effects. In a specific embodiment of the system, a specific method determines the single most-likely pronunciation of words. In further specific embodiments of the system, methods generate speaker-dependent pronunciation networks.