Abstract: A method (and system) of determining confusable list items and resolving this confusion in a spoken dialog system includes receiving user input, processing the user input and determining if a list of items needs to be played back to the user, retrieving the list to be played back to the user, identifying acoustic confusions between items on the list, changing the items on the list as necessary to remove the acoustic confusions, and playing unambiguous list items back to the user.

Abstract: An embodiment of the invention pertaining to a given task to be submitted for crowdsourcing computes an initial incentive range having minimum, maximum and midrange incentives, the maximum incentive being equal to a prespecified maximum incentive value. Historical data pertaining to tasks of the given type that were previously crowdsourced is acquired, wherein the historical data includes completion time and incentive information. The historical data is used with the minimum, midrange and maximum incentives to compute minimum, midrange and maximum incentive task completion times. These completion times are used to determine whether a first, second, or a third criterion has been met, and responsive to a first or second criterion being met, the given task is transformed, and the incentive range is updated, for use in computing a final incentive value.

Abstract: An embodiment of the invention is associated with a system disposed to post software related tasks to a crowdsourcing marketplace for execution. Prior to posting a specified task, it is determined whether the specified task comprises a complex task. Responsive to determining that the specified task comprises a complex task, the specified task is evaluated with respect to a first criterion, to determine whether the specified task should be decomposed into two or more atomic tasks. Responsive to determining that the specified task does not comprise a complex task, the specified task is evaluated with respect to a second criterion, to determine whether the specified task should be combined with other tasks into a bundled task.

Abstract: Systems and methods are provided to automatically determine culture-based behavioral tendencies and preferences of individuals in the context of customer service interactions. For example, systems and methods are provided to process natural language dialog input of an individual to detect linguistic features indicative of individualistic and collectivistic behavioral tendencies and predict whether such individual will be cooperative or uncooperative with automated customer service.

Abstract: Systems and methods are provided to automatically determine culture-based behavioral tendencies and preferences of individuals in the context of customer service interactions. For example, systems and methods are provided to process natural language dialog input of an individual to detect linguistic features indicative of individualistic and collectivistic behavioral tendencies and predict whether such individual will be cooperative or uncooperative with automated customer service.

Abstract: Systems and methods are provided to automatically determine culture-based behavioral tendencies and preferences of individuals in the context of customer service interactions. For example, systems and methods are provided to process natural language dialog input of an individual to detect linguistic features indicative of individualistic and collectivistic behavioral tendencies and predict whether such individual will be cooperative or uncooperative with automated customer service.

Abstract: Systems and methods are provided to automatically determine culture-based behavioral tendencies and preferences of individuals in the context of customer service interactions. For example, systems and methods are provided to process natural language dialog input of an individual to detect linguistic features indicative of individualistic and collectivistic behavioral tendencies and predict whether such individual will be cooperative or uncooperative with automated customer service.

Abstract: A method, system and computer readable device for recognizing a partial utterance in an automatic speech recognition (ASR) system where said method comprising the steps of, receiving, by a ASR recognition unit, an input signal representing a speech utterance or word and transcribing the input signal into text, interpreting, by a ASR interpreter unit, whether the text is either a positive or a negative match to a list of automated options by matching the text with a grammar or semantic database representing the list of automated options, wherein if the ASR interpreter unit results in said positive match proceeding to a next input signal and if the ASR interpreter unit results in said negative match rejecting the text as representing said partial utterance, and processing, by a linguistic filtering unit, the rejected text to derive a correct match between the rejected text and the grammar or semantic database.

Abstract: In one example, this invention presents a method of providing the same self-service content that is available on the web interface to users contacting by telephone, knowing that the web and telephone are fundamentally different user interfaces. In one embodiment, this patent seeks to protect the general idea of how to playback web data in real-time to the user over the speech interface. For this purpose, a method is presented comprising of the general steps through which the web data is initially sent to an automatic transformation module. Then, that transformation module refines or re-structures the web data to make it suitable for the speech interface. The algorithm in the module is predicated on the user interface principles of cognitive complexity and limitations on short term memory based on which FAQ types are classified into one of the following four classes: simple, medium, complex, and complex-complex.

Abstract: A method, system and computer readable device for recognizing a partial utterance in an automatic speech recognition (ASR) system where said method comprising the steps of, receiving, by a ASR recognition unit, an input signal representing a speech utterance or word and transcribing the input signal into text, interpreting, by a ASR interpreter unit, whether the text is either a positive or a negative match to a list of automated options by matching the text with a grammar or semantic database representing the list of automated options, wherein if the ASR interpreter unit results in said positive match proceeding to a next input signal and if the ASR interpreter unit results in said negative match rejecting the text as representing said partial utterance, and processing, by a linguistic filtering unit, the rejected text to derive a correct match between the rejected text and the grammar or semantic database.

Abstract: In one example, this invention presents a method of providing the same self-service content that is available on the web interface to users contacting by telephone, knowing that the web and telephone are fundamentally different user interfaces. In one embodiment, this seeks to protect the general idea of how to playback web data in real-time to the user over the speech interface. For this purpose, a method is presented comprising of the general steps through which the web data is initially sent to an automatic transformation module. Then, that transformation module refines or re-structures the web data to make it suitable for the speech interface. The algorithm in the module is predicated on the user interface principles of cognitive complexity and limitations on short term memory based on which FAQ types are classified into one of the following four classes: simple, medium, complex, and complex-complex.

Abstract: A method (and system) of determining confusable list items and resolving this confusion in a spoken dialog system includes receiving user input, processing the user input and determining if a list of items needs to be played back to the user, retrieving the list to be played back to the user, identifying acoustic confusions between items on the list, changing the items on the list as necessary to remove the acoustic confusions, and playing unambiguous list items back to the user.

Abstract: A method, system and computer readable device for recognizing a partial utterance in an automatic speech recognition (ASR) system where said method comprising the steps of, receiving, by a ASR recognition unit, an input signal representing a speech utterance or word and transcribing the input signal into text, interpreting, by a ASR interpreter unit, whether the text is either a positive or a negative match to a list of automated options by matching the text with a grammar or semantic database representing the list of automated options, wherein if the ASR interpreter unit results in said positive match proceeding to a next input signal and if the ASR interpreter unit results in said negative match rejecting the text as representing said partial utterance, and processing, by a linguistic filtering unit, the rejected text to derive a correct match between the rejected text and the grammar or semantic database.