International Business Machines Corporation

Ronald E Vanbuskirk

Huifang Wang

Kerry Alan Ortega

James Robert Lewis

Amado Nassiff

Peter J Guasti

Gary Robert Hanson

Arthur Keller

Harvey M Ruback

Steven Gary Woodward

Frank Fado

Barbara E Ballard

Daniel E Badt

Edwin A Rodriguez

Carl A Smith

Hans Egger

Stephane Herman Maes

Qing Gong

Keith P Loring

Catherine Gody Wolf

The method of identifying excess noise in a computer system includes first recording a silence sample; second recording an isolated noise sample while operating a computer system component in isolation from other computer system components; comparing signal characteristics of the silence sample with signal characteristics of the isolated noise sample; and, attributing the isolated noise sample to the isolated computer component when the signal characteristics of the silence sample differ by a preset threshold from the signal characteristics of the isolated noise sample. The inventive method can further include logging the signal characteristics of the silence sample and the isolated noise sample; reporting excess noise identified in the identifying step; and, suggesting a remedy for the identified excess noise.

Process for identifying excess noise in a computer system

A method of proofreading and correcting dictated text contained in an electronic document can include selecting proofreading criteria for identifying textual errors contained in the electronic document; playing back each word contained in the electronic document; and, marking as a textual error each played back word in nonconformity with at least one of the proofreading criteria.

Method and system for proofreading and correcting dictated text

A computer system has a notification manager for playing a message to a user by selecting one of a plurality of audio notifications. The method includes the step of setting a priority level for each notification arriving into a queue. The notification is inserted into a position in the queue based upon the priority level of the notification, such that the audio notifications at the queue top have a generally higher priority than audio notifications at the queue bottom. The notification at the top of the queue can be selected if the priority level of the notification is greater than a predetermined gate level. Once a notification is selected, a message corresponding to the selected notification is played to the user.

Audio notification management system

A transcription system ( ) includes a computer ( ), a monitor ( ), and a microphone ( ). Via the microphone, a user of the system provides input speech that is received and transcribed ( ) by the system. The system monitors ( ) the accuracy of the transcribed speech during transcription. The system also determines ( ) whether the accuracy of the transcribed speech is sufficient and, if not, automatically activates ( ) a speech recognition improvement tool and alerts ( ) the user that the tool has been activated.

Method and apparatus for improving speech recognition accuracy

A method of proofreading and correcting dictated text contained in an electronic document comprises the steps of: selecting proofreading criteria for identifying textual errors contained in the electronic document; playing back each word contained in the electronic document; and, marking as a textual error each played back word in nonconformity with at least one of the proofreading criteria. The method can further comprise the step of editing each the marked textual error identified in the marking step. In particular, the editing step can include reviewing each the marked textual error identified in the marking step; accepting user specified changes to each marked textual error reviewed in the reviewing step; and, unmarking each marked textual error corrected by the user in the accepting step. Also, the reviewing step can include highlighting each the word in the electronic document corresponding to the marked textual error marked in the marking step; and, displaying an explanation for each marked textual error in a user interface. Moreover, the reviewing step can further include suggesting a recommended change to the marked textual error; displaying the recommended change in the user interface; and, accepting a user specified preference to substitute the recommended change for the marked textual error.

A transcription system ( ) includes multiple recording devices ( ) that individually record and store ( ), into multiple files, digital data representing speech uttered by multiple speakers. In a preferred embodiment, time stamps are stored ( ) along with the speech. A transcription computer ( ) enables a user to select ( ) which of multiple files the user would like to have transcribed, and to associate ( ) a speaker ID to each of the multiple files. The transcription computer then transcribes ( ) phrases within the multiple files, and stores ( ) those phrases in a sequential order, based on the time stamps. The user may also cause an offset time for each file to be adjusted ( ), thus affecting the ultimate sequential order of the transcribed phrases. After transcription, the user may edit ( ) the time stamps, speaker IDs, and/or phrases.

Method and apparatus for transcribing multiple files into a single document

In a computer system having a list based natural discourse application adapted for speech recognition. In response to a first user element request, the system searches a list of elements to generate a list of matches which contain elements which satisfy the element request. The system calculates the time required to read out the match list common levels, the time required to read out all matches, and the time required to iteratively query the user as to which matches of one of said common levels to read out. The system then reads out the match list using the method having the lowest calculated time.

Method and apparatus for disambiguating lists of elements for speech interfaces

In a computer speech user interface, a method and computer apparatus for automatically adjusting the content of feedback in a responsive prompt based upon predicted recognition accuracy by a speech recognizer. The method includes the steps of receiving a user voice command from the speech recognizer; calculating present speech recognition accuracy based upon the received user voice command; predicting future recognition accuracy based upon the calculated present speech recognition accuracy; and, generating feedback in a responsive prompt responsive to the predicted recognition accuracy. For predicting future poor recognition accuracy based upon poor present recognition accuracy, the calculating step can include monitoring the received user voice command; detecting a reduced accuracy condition in the monitored user voice command; and, determining poor present recognition accuracy if the reduced accuracy condition is detected in the detecting step.

Method and system for automatically adjusting prompt feedback based on predicted recognition accuracy

In a computer system adapted for text-to-speech playback, a method for instructing a user in performing a task having a plurality of steps can include retrieving a textual instruction from a location in an electronic storage device of the computer system. The textual instruction can correspond to one or more of the steps in the task. The textual instruction can be displayed in a task automation user interface, and a text-to-speech (TTS) conversion of the textual instruction can be executed. The steps can be repeated until all textual instructions corresponding to each step in the task have been retrieved and TTS converted.

Task automation user interface with text-to-speech output

A transcription system ( ) includes a computer ( ), a monitor ( ), and a microphone ( ). Via the microphone, a user of the system provides input speech that is received and transcribed ( ) by the system. The system monitors ( ) the accuracy of the transcribed speech during transcription. The system also determines ( ) whether the accuracy of the transcribed speech is sufficient and, if not, automatically activates ( ) a speech recognition improvement tool and alerts ( ) the user that the tool has been activated. This tool could also be manually activated ( ) by the user. The type of recognition problem is identified ( ) by the user or automatically by the system, and the system provides ( ) possible solution steps for enabling the user to adjust ( ) system parameters or modify user behavior in order to alleviate the recognition problem. The system also provides the user the ability to test ( ) the transcription process in order to determine whether the solution has improved the recognition accuracy.

A dictation system ( ) performs a method of dictating speech which automatically activates ( ) and deactivates ( ) auxiliary topic libraries based on the input speech. After receiving ( ) input speech, the method searches ( ) a general library and topic libraries that are currently active, if any. The method also searches ( ) all or portions of inactive topic libraries. If the spoken word is recognized in a particular inactive topic library, the method automatically activates ( ) that topic library. In a preferred embodiment, the method maintains an adjustable &ldquo;score&rdquo; for each active topic library. An active library's score is increased ( ) each time a word is recognized in the library, and decreased ( ) when a word is recognized in another library. If the score falls below a certain threshold, the active topic library is automatically deactivated ( ).

Method and apparatus for activating and deactivating auxiliary topic libraries in a speech dictation system

A method and apparatus for transcribing text from multiple speakers in a computer system having a speech recognition application. The system receives speech from one of a plurality of speakers through a single channel, assigns a speaker ID to the speaker, transcribes the speech into text, and associates the speaker ID with the speech and text. In order to detect a speaker change, the system monitors the speech input through the channel for a speaker change.

Transcription system for multiple speakers, using and establishing identification

An efficient method and system, particularly well-suited for correcting natural language understanding (NLU) commands, corrects spoken commands misinterpreted by a speech recognition system. The method involves a series of steps, including: receiving the spoken command from a user; parsing the command to identify a paraphrased command; displaying the paraphrased command; and accepting corrections of the paraphrased command from the user. The paraphrased command is segmented according to command language categories, which include a command action category, an action object category, and an action and/or object modifying category. The paraphrased command is displayed in a user interface window segmented into these command language categories. The user interface window also contains alternative commands for each segment of the paraphrased command.

Method and apparatus for correcting misinterpreted voice commands in a speech recognition system

A method and system efficiently identifies voice commands for a user of a speech recognition system. The method involves a series of steps including: receiving input from a user; monitoring the computer system to log system events and ascertain a current system state; predicting a probable next event according to the current system state and logged events; and identifying acceptable voice commands to perform the next event. The system events include commands, system control activities, timed activities, and application activation. These events are statistically analyzed in light of the current system state to determine the probable next event. The voice commands for performing the probable next event are displayed to the user.

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Indiantown, FL, United States of America

Ronald E Vanbuskirk