Abstract: There is disclosed herein a computer-assisted method of identifying prompts from a batch of recorded interactive voice response (IVR) calls, including: identifying, within a call under analysis, a plurality of discrete utterances; electronically comparing a selected utterance to a set of known prompt candidates, wherein the known prompt candidates are candidates for being IVR prompts; based on the comparing, determining that the selected utterance clusters with a known prompt candidate cluster, and accumulating a counter for the prompt candidate cluster; and after processing the batch, identifying a set of good prompt candidates, wherein good prompt candidates have a counter above a threshold.

Abstract: There is disclosed, in an example, a computer-implemented system and method, which includes providing a large set of validation prompts; testing a first ML intent model with the large set of validation prompts, wherein the first ML intent model is to select for respective validation prompts a first intent from an intent set; testing a second ML intent model with the large set of validation prompts, wherein the second ML intent model is to select for the same validation prompts a second intent from the intent set; selecting a reduced set of validation prompts, comprising validation prompts for which the first intent and second intent do not match; receiving an analysis of the reduced set of validation prompts, including indicia of hits, wherein one of the ML intent models inferred a correct intent; and selecting as a preferred model an ML model of the first ML intent model or second ML model that provided more hits.

Abstract: There is disclosed a computer-implemented method of training an interactive voice assistant (IVA), including prompting an artificial intelligence (AI) to assume a persona and to seek to fill a service request by a service provider that operates the IVA; receiving, from the AI, a query for the IVA; providing the query to the IVA; receiving, from the IVA, a response to the query; continuing to permit the AI to query the IVA until the AI is satisfied that the IVA has filled the service request or that the IVA is unable to fill the service request; logging the queries and responses between the AI and the IVA; and based on the logging, debugging or improving the IVA.

Abstract: There is disclosed a computer-implemented method, including receiving, from a human user, a natural language query; modifying the natural language query (a modified query) and posting the modified query to a general-purpose artificial intelligence (AI); receiving, from the general-purpose AI, a raw response to the modified query; providing the raw response to a plurality of guardrail AIs, wherein the guardrail AIs are to provide domain-specific evaluations of the raw response; receiving, from the plurality of guardrail AIs, the domain-specific evaluations; forwarding a version of the raw response to the human user; and acting on the domain-specific evaluations.

Abstract: Systems and methods that analyze and monitor the performance of a call center including performance of the interactive voice response systems, call center agents, and other components. The systems and methods record characteristics of the call such as the audio data, and analyze that record to identify the events that take place during the call. These events may be defined as customer/call center interactions, such as dropped calls, logic errors or other event. A call center administrator may also identify a set of metrics, such as the number of dropped calls that occur during a day, that may be monitored by the systems described herein. The data collected about these events and metrics may be stored in a database and provided to the administrator through a user interface that allows the administrator to browse through the collected metric and recorded call data and directly review relevant portions of a call.

Abstract: Systems and methods that, among other things, analyze and monitor the performance of a call center including performance of the interactive voice response (IVR) systems, call center agents, and other components of the call center. The systems and methods record characteristics of the call such as the audio data, and analyze that record to identify the events and the actions that take place during the call. A call center administrator may also identify a set of metrics, such as the number of dropped calls that occur during a day that may be monitored by the systems described herein. The data collected about these events and the resulting metrics may be stored in a database and provided to a call center administrator through a user interface that allows the administrator to browse through the collected metric and recorded call data and directly review relevant portions of a call.

Abstract: Systems and methods that, among other things, analyze and monitor the performance of a call center including performance of the interactive voice response (IVR) systems, call center agents, and other components of the call center. The systems and methods record characteristics of the call such as the audio data, and analyze that record to identify the events and the actions that take place during the call. A call center administrator may also identify a set of metrics, such as the number of dropped calls that occur during a day that may be monitored by the systems described herein. The data collected about these events and the resulting metrics may be stored in a database and provided to a call center administrator through a user interface that allows the administrator to browse through the collected metric and recorded call data and directly review relevant portions of a call.

Abstract: Systems and methods that, among other things, analyze and monitor the performance of a call center including performance of the interactive voice response (IVR) systems, call center agents, and other components of the call center. The systems and methods record characteristics of the call such as the audio data, and analyze that record to identify the events and the actions that take place during the call. These events and actions may be defined as complex customer/call center interactions, such as dropped calls, logic errors or other event. A call center administrator may also identify a set of metrics, such as the number of dropped calls that occur during a day or for each agent, the number of times a client was left on hold for more than two minutes, or other such metrics that may be monitored by the systems described herein.

Abstract: A system and method for routing telephone calls is based on identifying caller goals, and maximizing the benefit of routing the call to the appropriate call center. The appropriate call center is identified as the call center best equipped to respond to the needs of the caller. The cost or benefit is based on the fastest and least expensive way to answer a query posed by a caller. A probabilistic model of the caller's goals or call topics based on a response to a top-level prompt is used, along with a set of functions associating a utility or benefit with routing those call topics to destinations within the center. Maximum benefit routing allows for the separation of the caller's goals from those of the call center, thereby optimizing use of available resources.

Abstract: A code signal representing a sequence of code symbols carrying digital information is generated with the frequency components of the code signal being essentially confined to a preselected signalling band lying within the bandwidth of an audio signal within which the code signal is to be embedded. The audio signal is continuously frequency analyzed over a frequency band encompassing the signalling band and the code signal is dynamically filtered as a function of the analysis thereby to provide a modified code signal with frequency components which are, at each time instant, essentially a preselected small proportion of the levels of the corresponding audio signal frequency components. Accordingly, the modified code signal can be combined with the audio signal to obtain a composite audio signal which is not readily distinguishable from the original audio signal by listening.

Abstract: The invention provides an adaptive noise cancelling apparatus which operates to overcome a problem encountered in conventional noise cancelling circuitry when the signal-to-noise ratio at the sensor array is high--to wit, that the target signal is degraded, leading to poorer intelligibility. An apparatus constructed in accord with the invention selectively inhibits the adaptive filter from changing its filter values in these instances and, thereby, prevents it from generating a noise-approximating signal that will degrade the target component of the output signal.