Abstract: A system for processing analytics on a cluster of computing resources may receive a user request to process a Job, Service or Reservation, and may include an Orchestrator, Resource Manager, Process Manager, and one or more Agents and Job Drivers, which together deploy the Job onto one or more nodes in the cluster for parallelized processing of Jobs and their associated work items.

Abstract: A system for processing analytics on a cluster of computing resources may receive a user request to process a Job, Service or Reservation, and may include an Orchestrator, Resource Manager, Process Manager, and one or more Agents and Job Drivers, which together deploy the Job onto one or more nodes in the cluster for parallelized processing of Jobs and their associated work items.

Abstract: Techniques are disclosed for overcoming errors in speech recognition systems. For example, a technique for processing acoustic data in accordance with a speech recognition system comprises the following steps/operations. Acoustic data is obtained in association with the speech recognition system. The acoustic data is recorded using a combination of a first buffer area and a second buffer area, such that the recording of the acoustic data using the combination of the two buffer areas at least substantially minimizes one or more truncation errors associated with operation of the speech recognition system.

Abstract: Techniques are disclosed for overcoming errors in speech recognition systems. For example, a technique for processing acoustic data in accordance with a speech recognition system comprises the following steps/operations. Acoustic data is obtained in association with the speech recognition system. The acoustic data is recorded using a combination of a first buffer area and a second buffer area, such that the recording of the acoustic data using the combination of the two buffer areas at least substantially minimizes one or more truncation errors associated with operation of the speech recognition system.

Abstract: Techniques are disclosed for overcoming errors in speech recognition systems. For example, a technique for processing acoustic data in accordance with a speech recognition system comprises the following steps/operations. Acoustic data is obtained in association with the speech recognition system. The acoustic data is recorded using a combination of a first buffer area and a second buffer area, such that the recording of the acoustic data using the combination of the two buffer areas at least substantially minimizes one or more truncation errors associated with operation of the speech recognition system.

Abstract: In a computer speech recognition system, the present invention provides a method and system for recognizing and executing a voice command that has a dictation portion. Upon receiving a user input, the spoken utterance is processed to identify a pattern of words which matches a pre-determined command pattern. Then, computer system command is identified that corresponds to the pre-determined command pattern and has at least one parameter. The parameter is extracted from a dictation portion of the spoken utterance which is separate from the pattern of words matching the command pattern. The computer system command is then processed to perform an event in accordance with the parameter. If the spoken utterance does not contain a pattern of words matching a pre-determined command pattern, then the spoken utterance is recognized as dictation and inserted at a specified location into an electronic document or other system or application software.

Abstract: A speech input method editor can include a speech toolbar (102) having at least a microphone state/toggle button (104). The speech input method editor can also include a selectable dictation window area (108) used as a temporary dictation target until dictation text is transferred to a target application and a selectable correction window area (112) having at least one among an alternate list (120) for correcting dictated words, an alphabet (114), a spacebar (116), a spell mode reminder (118), or a virtual keyboard (122). The speech input method editor can remain active while using the selectable correction window and while transferring dictation text to the target application. The speech input method editor can further include an alternate input method editor window (112b) used to allow non-speech editing into at least one among the dictation window or to the target application while using the speech input method editor.

Abstract: A method for automatically analyzing a document in a speech recognition system having a vocabulary and language model can include the steps of: determining whether the document has undergone previous analysis; undoing the previous analysis; and, analyzing the document. More specifically, the determining step comprises the steps of: comparing trigrams in the document with trigrams in the language model; and, setting a reference point containing document data for undoing a previous analysis in the undoing step if the compared language model contains all the document trigrams. Moreover, the undoing step comprises the step of removing from the language model each trigram contained in the document data in the reference point.

Abstract: In this speech recognition system, the size of the language model is reduced by discarding those n-grams that the acoustic part of the system can recognize most accurately without support from a language model. The n-grams can be discarded dynamically during the running of the system or during the build or setup-time of the system. Trigrams occurring infrequently in the text corpora are substituted for the discarded n-grams to increase the accuracy of the word recognitions.