A computer based system and method for identifying complaint interactions, including: detecting appearances of linguistic structures related to complaints in an interaction; calculating at least one sentiment metric of the interaction; and classifying the interaction as being or not being a complaint interaction based on the detected linguistic structures and the at least one sentiment metric, for example using a trained supervised learning model.

A computer based system and method for identifying complaint interactions, including: detecting appearances of linguistic structures related to complaints in an interaction; calculating at least one sentiment metric of the interaction; and classifying the interaction as being or not being a complaint interaction based on the detected linguistic structures and the at least one sentiment metric, for example using a trained supervised learning model.

Method starts with a processor receiving configuration settings including an identified task, a relationship data, and a criticality value. Processor initializes a communication session with an agent client device. The communication session is between a virtual caller associated with the system and the agent client device. Processor then processes an audio signal of the communication session to generate an agent utterance and generates a transcribed agent utterance based on the agent utterance using a speech-to-text processor. Processor generates a virtual caller utterance using a task-specific virtual caller neural network associated with the identified task. The virtual caller utterance can be generated based on the transcribed agent utterance. Processor then causes the virtual caller utterance to be played back in the communication session to the agent client device. Other embodiments are disclosed herein.

Method starts with a processor receiving configuration settings including an identified task, a relationship data, and a criticality value. Processor initializes a communication session with an agent client device. The communication session is between a virtual caller associated with the system and the agent client device. Processor then processes an audio signal of the communication session to generate an agent utterance and generates a transcribed agent utterance based on the agent utterance using a speech-to-text processor. Processor generates a virtual caller utterance using a task-specific virtual caller neural network associated with the identified task. The virtual caller utterance can be generated based on the transcribed agent utterance. Processor then causes the virtual caller utterance to be played back in the communication session to the agent client device. Other embodiments are disclosed herein.

Method starts with a processor receiving configuration settings including an identified task, a relationship data, and a criticality value. Processor initializes a communication session with an agent client device. The communication session is between a virtual caller associated with the system and the agent client device. Processor then processes an audio signal of the communication session to generate an agent utterance and generates a transcribed agent utterance based on the agent utterance using a speech-to-text processor. Processor generates a virtual caller utterance using a task-specific virtual caller neural network associated with the identified task. The virtual caller utterance can be generated based on the transcribed agent utterance. Processor then causes the virtual caller utterance to be played back in the communication session to the agent client device. Other embodiments are disclosed herein.

Method starts with a processor receiving configuration settings including an identified task, a relationship data, and a criticality value. Processor initializes a communication session with an agent client device. The communication session is between a virtual caller associated with the system and the agent client device. Processor then processes an audio signal of the communication session to generate an agent utterance and generates a transcribed agent utterance based on the agent utterance using a speech-to-text processor. Processor generates a virtual caller utterance using a task-specific virtual caller neural network associated with the identified task. The virtual caller utterance can be generated based on the transcribed agent utterance. Processor then causes the virtual caller utterance to be played back in the communication session to the agent client device. Other embodiments are disclosed herein.

Various techniques described herein relate to analyzing and redacting information from customer interaction records such as call transcripts, to support transmission of the interaction records from a secured environment to various external analytics systems. Transcript texts may be received and processed by a redaction system, during which the transcript texts may be analyzed to generate conversations and convert numerical texts into numbers. One or more regular expressions defining search and replace patterns may be selected and used to redact confidential or sensitive information from the transcripts. In various implementations, the regular expressions used to redact transcripts may be determined or generated based on transcript categorization, the security characteristics of the transmission networks and/or external systems to which the redacted transcripts are to be transmitted, and/or other attributes of the transcript or the associated systems.

Various techniques described herein relate to analyzing and redacting information from customer interaction records such as call transcripts, to support transmission of the interaction records from a secured environment to various external analytics systems. Transcript texts may be received and processed by a redaction system, during which the transcript texts may be analyzed to generate conversations and convert numerical texts into numbers. One or more regular expressions defining search and replace patterns may be selected and used to redact confidential or sensitive information from the transcripts. In various implementations, the regular expressions used to redact transcripts may be determined or generated based on transcript categorization, the security characteristics of the transmission networks and/or external systems to which the redacted transcripts are to be transmitted, and/or other attributes of the transcript or the associated systems.

A remote work support system includes a wearable device worn by a site worker, a mobile terminal carried by the site worker separately from the wearable device, and a support operator terminal used by a support operator who remotely supports the site worker. The wearable device includes an image capturing unit, a voice input unit, and a voice output unit. The wearable device transmits an image. The wearable device transmits and receives voice. The mobile terminal includes a display unit to display a received image. The support operator terminal includes a voice input unit, a voice output unit, and a display unit. The support operator terminal transmits and receive voice to and from the wearable device. The support operator terminal receives an image from the wearable device. The support operator terminal transmits an image to the mobile terminal.

An electronic device includes a controller. The controller performs a voice recognition operation on a voice uttered by a person being monitored. The controller generates emotion information for the person being monitored, based on the voice recognition operation.