Abstract: Embodiments relate to providing task assistance. One aspect includes collecting sensor data from a sensor that is communicatively coupled to a computer device, and receiving inputs from a user of the device. The inputs are directed to implementation of tasks via applications operated on the device. Another aspect includes determining a cognitive state of the user from the sensor data and the inputs for each of the tasks performed and calculating a normative cognitive state of the user that is represented as a value within a range of values. A further aspect includes selecting a task assist function responsive to initiation of a task by the user at the device. The task assist function is selected based on a deviation of a value representing a current determined cognitive state from the normative cognitive state value.

Abstract: Embodiments relate to providing task assistance. One aspect includes collecting sensor data from a sensor that is communicatively coupled to a computer device, and receiving inputs from a user of the device. The inputs are directed to implementation of tasks via applications operated on the device. Another aspect includes determining a cognitive state of the user from the sensor data and the inputs for each of the tasks performed and calculating a normative cognitive state of the user that is represented as a value within a range of values. A further aspect includes selecting a task assist function responsive to initiation of a task by the user at the device. The task assist function is selected based on a deviation of a value representing a current determined cognitive state from the normative cognitive state value.

Abstract: A method for a speech response system to automatically transfer users to human agents. The method can establish an interactive dialog session between a user and an automated speech response system. An error score can be established when the interactive dialog session is initiated. During the interactive dialog session, responses to dialog prompts can be received. Error weights can be assigned to receive responses determined to be non-valid responses. Different non-valid responses can be assigned different error weights. For each non-valid response, the assigned error weight can be added to the error score. When a value of the error score exceeds a previously established error threshold, a user can be automatically transferred from the automated speech response system to a human agent.

Abstract: A method (50) of dynamically changing a sentence structure of a message can include the step of receiving (51) a user request for information, retrieving (52) data based on the information requested, and altering (53) among an intonation and/or the language conveying the information based on the context of the information to be presented. The intonation can optionally be altered by altering (54) a volume, a speed, and/or a pitch based on the information to be presented. The language can be altered by selecting (55) among a finite set of synonyms based on the information to be presented to the user or by selecting (56) among key verbs, adjectives or adverbs that vary along a continuum.

Abstract: A method for a speech response system to automatically transfer users to human agents. The method can establish an interactive dialog session between a user and an automated speech response system. An error score can be established when the interactive dialog session is initiated. During the interactive dialog session, responses to dialog prompts can be received. Error weights can be assigned to receive responses determined to be non-valid responses. Different non-valid responses can be assigned different error weights. For each non-valid response, the assigned error weight can be added to the error score. When a value of the error score exceeds a previously established error threshold, a user can be automatically transferred from the automated speech response system to a human agent.

Abstract: A method for a speech response system to automatically transfer users to human agents. The method can establish an interactive dialog session between a user and an automated speech response system. An error score can be established when the interactive dialog session is initiated. During the interactive dialog session, responses to dialog prompts can be received. Error weights can be assigned to receive responses determined to be non-valid responses. Different non-valid responses can be assigned different error weights. For each non-valid response, the assigned error weight can be added to the error score. When a value of the error score exceeds a previously established error threshold, a user can be automatically transferred from the automated speech response system to a human agent.

Abstract: A method, a system, and an apparatus for efficiently presenting correction options. The present invention is capable of analyzing user voice commands and sorting multiple input requests based on user selection probability to determine whether a confirmation step should be presented and, if so, the manner in which the confirmation step should be presented. In particular, the method requests an information input from the user and then assigns a confidence level to the information input. If the confidence level is LOW, then the system performs an immediate confirmation step. If the confidence level assigned is MEDIUM or HIGH, then the information is placed into a data set that is confirmed in a batch confirmation step. The batch confirmation step presents the captured information to the user for confirmation. If any of the information is incorrect, then the method sorts the information in ascending order by confidence level and creates a menu of items that may be changed. The user then makes the change.

Abstract: A system and methods are provided for conducting an interactive dialog via a speech-based user interface. The system includes an auditory prompt module for generating a sequence of goal-directed auditory prompts based upon a pre-determined user-oriented task, and an error recovery module for responding to a communication error by initiating an error recovery based upon a user response to the sequence of goal-directed auditory prompts. The error recovery includes providing at least one error-recovery prompt selected from a hierarchy of error-recovery prompts, the selection based upon a hierarchy of communication error types.

Abstract: In a speech recognition system, a method of nonvisual enrollment comprising playing an audio representation of an enrollment script. As the enrollment is playing, shadowed speech from a user can be received, wherein the shadowed speech can lag the enrollment script. The received shadowed speech can be recorded for enrolling the user into the speech recognition system.

Abstract: A method of generating a grammar for recognizing headings in a speech recognition system can include identifying, within a data store, at least one heading selection associated with a content item. At least a first word from the identified heading selections can be extracted and a heading grammar automatically can be generated by including each extracted word of the identified heading selections within the heading grammar.

Abstract: In a speech recognition system, a method of nonvisual enrollment comprising playing an audio representation of an enrollment script. As the enrollment is playing, shadowed speech from a user can be received, wherein the shadowed speech can lag the enrollment script. The received shadowed speech can be recorded for enrolling the user into the speech recognition system.

Abstract: A method of generating a grammar for recognizing headings in a speech recognition system can include identifying, within a data store, at least one heading selection associated with a content item. At least a first word from the identified heading selections can be extracted and a heading grammar automatically can be generated by including each extracted word of the identified heading selections within the heading grammar.