Abstract: Disclosed herein are system, method, and computer program product embodiments for machine learning systems to process incoming call-center calls based on caller preferences. Text of historical interactive communications of a set of first callers are used to train one or more machine learning models to extract caller preferences. These trained models extract caller preferences for a second caller to generate a customer specific profile. An automated call center assistance system is configured to selectively route, based on the customer specific profile, a current call from the second caller to a call center agent and communicate one or more of the caller preferences for the second caller to the call center agent for consideration in an interactive communication during the current call.

Abstract: Aspects of the present disclosure relate to evaluating a contact center agent using an automated evaluation process that employs aspects of machine learning to review pieces of content, identify context within a piece of content where a compliance statement is required, and determine if a compliance statement was given by the agent. In some embodiments, a compliance model is trained and utilized to recognize context within the customer-agent interaction indicating that a compliance statement should be given by the agent. The presence or absence of a compliance statement in the piece of content may then be evaluated by the model and reported to the contact center supervisor. The automated nature of the invention efficiently and effectively reduces the unnecessary randomness introduced by a manual review process while providing improved assurance that compliance requirements are consistently provided during customer interactions.

Abstract: A computer based system and method for automatically detecting frustration in an interaction, may include: identifying in the interaction using a set of linguistic rules, natural language patterns related to frustration, wherein the linguistic rules further define weights associated with the natural language patterns and rule metadata; reviewing the rule metadata associated with the identified natural language patterns to identify override attributes, wherein if the rule metadata does not include override attributes, then a frustration level in the interaction is determined based on the identified natural language patterns and weights associated with the identified natural language patterns; and if the rule metadata includes override attributes than the frustration level is determined based on the identified override attributes.

Abstract: Electronic communication methods and systems for determining sentiment associated with a communication, conveniently displaying indicia of the sentiment information, and scoring the sentiment information are disclosed. The methods and systems can include associating an emoji with a sentiment and annotating information, for example, a highlight reel or a waveform, with the emoji.

Abstract: A resource managing computer system for managing at least one resource in an enterprise is disclosed. The resource managing computer system includes a communication interface for establishing at least one web based chat communication session with at least one customer. The system further includes a monitoring module for monitoring one or more parameters associated with the at least one web based chat communication session. The system further includes a computing module for computing at least one confidence score based on the one or more monitored parameters of the at least one web based chat communication session. The system further includes an allocation module for allocating the at least one resource to the at least one web based chat communication session, wherein the allocation is performed based on the at least one computed confidence score.

Abstract: The communication system includes a communication unit that receives a conversation of a user, an accumulation unit that accumulates a conversation frame that describes a structure of a conversation generated on a basis of the conversation of the user collected via the communication unit, and a control unit that obtains a feeling parameter related to a feeling of the user who sends the conversation in units of the collected conversation. The control unit further extracts the conversation frame from the conversation on a basis of the feeling parameter, and accumulates the conversation frame in the accumulation unit.

Abstract: A system obtains conversation data corresponding to conversations between users and agents of a client. The system identifies a set of intents from the conversations and identifies a set of contexts, explicit elements, and implied elements of these intents. The system identifies actions that can be performed to recognize new explicit and implied elements from new conversations and to address intents in these new conversations. Based on these actions, the system generates a set of recommendations that can be provided to the client. As agents communicate with users, the system monitors adherence to the set of recommendations.

Abstract: A system for aggregating sentiment analysis of communications between a plurality of entity groups is provided. The system may include a plurality of entity groups. Each entity group may include one entity, two entities or a plurality of entities. The system may include a plurality of communications. Each of the communications may be transmitted from a first entity. A first entity group may include the first entity. The plurality of entity groups may include the first entity group. Each of the communications may be transmitted to a second entity. The second entity may be included in a second entity group. The second entity group may be included in the plurality of entity groups. The system may also include a sentiment score determination module. The sentiment score determination module may determine an aggregate sentiment score for the plurality of communications. The sentiment score may determine a communication threat level.

Abstract: Electronic communication methods and systems for determining sentiment associated with a communication, conveniently displaying indicia of the sentiment information, and scoring the sentiment information are disclosed. The methods and systems can include associating an emoji with a sentiment and annotating information, for example, a highlight reel or a waveform, with the emoji.

Abstract: There is provided an information processing system including a storage section that holds a plurality of agent programs with different attributes, a communication section that provides an agent service by the agent programs to a client terminal of a user, and a control section that selects, from among the plurality of agent programs, one agent program suited to an emotion of a user who can use the agent service.

Abstract: Systems and methods for natural language processing and classification are provided. In some embodiments, the systems and methods include a communication editor dashboard which receives the message, performs natural language processing to divide the message into component parts. The system displays the message in a first pane with each of the component parts overlaid with a different color, and displaying in a second pane the insights, the confidence scores associated with each insight, the sentiment and the actions. In another embodiment, the systems and methods include combining outputs from multiple machine learned AI models into a unified output. In another embodiment, the systems and methods include responding to simple question using natural language processing.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: Implementations are directed to methods for providing an enhanced encounter via a holographic virtual assistant, including detecting, by one or more processors, an encounter request from a user, selecting a first encounter including a first holographic representation and a first dialog output, providing the first encounter for presentation to the user on the holographic virtual assistant, receiving, from the user, a first user reaction, the first user reaction including a first user dialog input and a first user engagement input, and training, using the first user reaction, a conversational goal model.

Abstract: A conversation may be monitored in real time using a trained machine learning model to identify a desired outcome of a conversation and generate one or more phrases for accomplishing the desired outcome. A confidence score may also be determined for one or more phrases that indicates a likelihood that the one or more phrases may help accomplish the desired outcome of the conversation. In some examples, a confidence score may be based on whether an agent, a caller, or both responded unfavorably to a similar phrase used previously in another conversation. In other examples, a confidence score corresponding to one or more phrases may be based on whether a prior conversation in which one or more similar phrases was used resulted in the desired outcome being accomplished.

Abstract: The communication system includes a communication unit that receives a conversation of a user, an accumulation unit that accumulates a conversation frame that describes a structure of a conversation generated on a basis of the conversation of the user collected via the communication unit, and a control unit. The control unit obtains a feeling parameter related to a feeling of the user who sends the conversation in units of collected conversation, extracts the conversation frame from the conversation on a basis of the feeling parameter, and accumulates the conversation frame in the accumulation unit.

Abstract: A method, computer program product and computer system for recovering from a likely exit condition in an electronic conversation with a user and interactive agent is provided. A processor retrieves one or more messages from a conversation between a user and an interactive agent. A processor determines at least one label for the one or more messages between a user and an interactive agent. A processor compares the at least one label for the one or more messages to a sequence model. A processor identifies the one or more messages from the conversation indicate an exit condition for the user based on the comparison of the at least one label for the one or more messages to the sequence model. A processor sends a recovery message to the user to redirect the conversation.

Abstract: A natural language processing system for analyzing speech includes a computer processing device configured to receive recorded speech of a person. The computer processing device constructs a baseline speech model of the person, the baseline speech model of the person including a property of speech based on a personal attribute of the person, compares current recorded speech of the person to the baseline speech model of the person to determine a deviation of the property of speech therebetween, and determines if the deviation of the property of speech meets a threshold of the property of speech that is defined for a disorder.

Abstract: Aspects of the disclosure relate to using machine learning for optimized call routing. A computing platform may receive requests to establish a voice call session. Based on corresponding phone numbers, the computing platform may identify demographic information for corresponding clients. Using a machine learning model and based on the demographic information and representative performance data, the computing platform may score potential client-representative combinations to indicate likelihoods of a successful outcome resulting from establishing a voice call session between the respective client and representative. Scoring the potential client-representative combinations may be based on fall off rates, indicating changes in representative effectiveness as hold time increases. The computing platform may adjust the scores based on a historical frequency of interaction between each representative and clients corresponding to the identified demographic information.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: A system and method for generating an agent behavioral analytics including transcribing an incoming call to produce a call transcription; and using a trained convolutional neural network (CNN) to produce behavioral labels for the agent in the incoming call for behavioral metrics, based on the call transcription. The CNN may include an embedding layer to convert words in the call transcription into vectors in a word embedding space; a convolution layer to perform a plurality of convolutions on the vectors and to generate vectors of features; a pooling layer to concatenate the vectors of features to a single vector by taking a maximum of each feature generated by the convolution layer; and a classification layer to produce grades of the agent in the incoming call for the set of attributes or behavioral metrics, based on the single vector generated by the pooling layer.

Abstract: A system and method for supporting a service representative during a call with a user is disclosed. The system and method include using an intelligent voice assistant to monitor the call between the user and representative. The intelligent voice assistant may provide suggested actions when detecting a request from the user or service representative. The intelligent voice assistant can provide transcripts, call logs and/or call summary information to the service representative or user. The intelligent voice assistant can monitor a user's environment and speech to determine a stress level and/or user sentiment.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: Techniques are described for analyzing communications sent during a service session to provide (e.g., customer) service on a social media channel, the analysis to determine a quality of service provided during the session. Natural language processing, lexical analysis, pattern matching, or other types of analysis may be used to determine an empathy factor and a conversational factor for communications between a service representative (SR) and a user during a session. The factors may be combined with other factors, such as a timely acknowledgement factor and a timely resolution factor, to generate a response quality index (RQI) for the session. Based on the RQI, feedback information may be generated and sent to the SR. In some implementations, the communications may be analyzed and feedback information sent to the SR in real time during the session, to dynamically improve service quality.

Abstract: A process for updating a second agent about a call in a contact center comprises receiving a call at the contact center and connecting the call to a device associated with a first agent of the contact center. A processor is used to configure a list of keywords to detect during the call, and when a key word is detected (e.g., using a speech analyzer), a snippet of the call based on the detected keywords is identified. The snippets are presented to a second agent through a device associated with the second agent. The call is then connected to the device associated with the second agent.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: Apparatus and methods consistent with the present invention measure one or more of the characteristics of a voice recording and use such measurements to create a synthetic voice that approximates the recorded voice and uses such created synthetic voice to verbalize the content of an electronically conveyed written message such as an SMS text message. The vocal characteristics measured may include frequency, timbre, intensity, rhythm, and rate of speech as well as others.

Abstract: The APPARATUSES, METHODS AND SYSTEMS FOR A DIGITAL CONVERSATION MANAGEMENT PLATFORM (“DCM-Platform”) transforms digital dialogue from consumers, client demands and, Internet search inputs via DCM-Platform components into tradable digital assets, and client needs based artificial intelligence campaign plan outputs. In one implementation, The DCM-Platform may capture and examine conversations between individuals and artificial intelligence conversation agents. These agents may be viewed as assets. One can measure the value and performance of these agents by assessing their performance and ability to generate revenue from prolonging conversations and/or ability to effect sales through conversations with individuals.

Abstract: A method, a computer program product, and an information handling system is provided for reducing cost and improving real-time performance for analyzing and representing customer care communication progression based on tone assessments by monitoring communications between a plurality of customers and a plurality of representatives to form a plurality of interaction histories. Analyzing a text form of the plurality of interaction histories according to a Tone Latent Dirichlet Allocation [T-LDA] model to determine a plurality of conversation tones. Mapping the plurality of conversation tones to a plurality of conversation phases and providing a representation of the conversation tones identifying a first customer tone at a first conversation phase and a second customer tone at a second conversation phase.

Abstract: At least some embodiments, a system includes a memory, and a processor configured to convert an audio stream of a speech of a customer during a customer call session into customer-originated text. The customer-originated text is displayed in a first chat interface. A request from a first call center agent is sent to a second call center agent via the first chat interface to interact with the customer during the customer call session and displayed in a second chat interface. The second agent is allowed to participate in the customer call session when the second call center agent accepts the request from the first call center agent. First agent-originated text and second agent-originated text during the customer call session is merged to form a combined agent-originated text and synthesized to computer-generated agent speech having a voice of a computer-generated agent based on the combined agent-originated text communicated to the customer over the voice channel.

Abstract: The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.

Abstract: Managing access to confidential content is provided. An indication of an identity of a teleconference participant is received via a voice communication headset that includes a skull conduction speaker and microphone. A database is analyzed to identify confidential information the teleconference participant is not authorized to hear. Voice communication content is provided in real time to the teleconference participant. The identified confidential information the teleconference participant is not authorized to hear is muted in the voice communication content.

Abstract: A call processing system and method for providing a secondary information channel to a caller. Upon reception of a call from a caller to a customer service representative on a primary access channel determine a device (secondary device) associated with the caller that is separate from the device the caller is using for the primary access channel. The secondary device is to be used to provide a secondary information access channel. The secondary information access channel is complimentary to the primary access channel between the caller and the customer service representative and is utilized to deliver information content to the caller and/or provide other services supportive of the conversation with the company service representative.

Abstract: A real-time speech analytics system (“RSTA system”) detects a speech condition during a call involving a contact center agent and a remote party. Upon detecting the speech condition, an alert message is provided to an alert reporting module (“ARM”), which is configured to access various data to form a RTSA alert. In one embodiment, the RTSA alert is a transient alert indication overlaid on an agent icon on a grid where the agent icon represents the agent and is displayed to a contact center supervisor. Information on the type and severity of the alert may be conveyed by text and non-text images, such as icons, colors, or symbols. A number representing a cumulative number of alert messages received for each agent may be indicated in an alert bubble overlaid on the agent icon. A viewer is able to request detailed alert data upon selecting the alert bubble.

Abstract: A system and method are presented for body language analysis of a video interaction. In a contact center system, the video interaction between an agent and a customer may be monitored and used to determine automatic actions when threshold are met and/or matches are made. Training videos comprising determined metrics may be used for comparison to real-time interactions. Scoring and/or matches may be utilized to determine a threshold to trigger pre-determined actions based on comparison to the training videos.

Abstract: An action item identification system automatically determines action items by analyzing conversations of representatives with customers. The action item identification system retrieves recordings of various conversations, extracts features of each of the conversations, and analyzes the features to determine a set of features that is indicative of an action item associated with the corresponding conversation. The set of features is further analyzed to generate the action item in an action item manifest (a) as a summary of what is discussed in the conversations or (b) verbatim from the conversations.

Abstract: The redaction process/system operates on temporarily captured/saved audio file during an agent-customer-call center (CC) call. Voice-based audio data is captured and processed by monitoring data input from CC-agent into a defined data field (field in a CC-agent-presented form). The redact process generates a start-record time based upon initial data input into the field and further generates an end-of-recording (“EOR”) time for the field. The audio file is filtered and segments are permanently saved audio data (A-data) bounded by the start-record and EOR times. Thereafter, all stored audio data is deleted (preferably crypto-shredded) except the saved A-data to substantially eliminate retrieval of initially stored audio data. An IVR process can be used to trigger record ON/OFF instructions. Audio file segments can be trimmed with precursive and successive time periods to move the start and end times of the audio segments. System Operator sets time-trim periods.

Abstract: The methods, apparatus, and systems described herein are designed to route customer communications to the best agent or best available agent. The methods include receiving a customer communication, predicting a demographic profile of the customer associated with the customer communication, monitoring real-time agent performance data and modifying a predetermined work threshold based on the real-time agent performance data, and providing a routing recommendation to route the customer to an agent based on the prediction and historical customer data for agents who have not exceeded the predetermined work threshold.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, a voicemail device having a controller to detect a recording of a voicemail message, generate a Session Initiation Protocol (SIP) message, wherein the SIP message contains visual voicemail data associated with the recorded voicemail message, and transmit the SIP message to a cordless phone system, wherein the SIP message is received by the cordless phone system over a data port of the cordless phone system, wherein the cordless phone system comprises a base station and at least one cordless communications device, wherein the visual voicemail data is retrieved by the base station, and wherein the visual voicemail data is transmitted by the based station to the at least one cordless communications device by utilizing a cordless wireless access protocol. Other embodiments are disclosed.

Abstract: An improved technique of processing an electronic transaction is disclosed. In the improved technique, a validation operation is performed on a set of standard user input and a set of peripheral device data received by a server connected to a client computer, the validation operation verifying a link between the set of standard user input and the set of peripheral device data. Based on results of the validation operation, an authorization code is assigned to the electronic transaction.

Abstract: Apparatus and methods consistent with the present invention measure one or more of the characteristics of a voice recording and use such measurements to create a synthetic voice that approximates the recorded voice and uses such created synthetic voice to verbalize the content of an electronically conveyed written message such as an SMS text message. The vocal characteristics measured may include frequency, timbre, intensity, rhythm, and rate of speech as well as others.

Abstract: An architecture is provided for handling event notifications generated by a speech analytics module (“SAM”) that recognizes keywords present in the audio of a call between an agent in a contact center and a remote party. In one embodiment, an event handler module receives and forwards the event notifications to various application specific modules (“ASMs”). The forwarding process may vary on the content and/or type of event notification received. Each ASM performs the processing for a particular audio context and may generate call instance data that pertains to the audio context and indicates whether the agent complied with various requirements during the call. The call instance data may be stored in a file for evaluating the agent's performance. The ASM may also perform other actions as appropriate, such as providing visual indicators on the agent's computer desktop or notify the agent's supervisor.

Abstract: A real-time speech analytics system (“RSTA system”) detects a speech condition during a call involving a contact center agent and a remote party. Upon detecting the speech condition, an alert message is provided to an alert reporting module (“ARM”), which is configured to access various data to form a RTSA alert. In one embodiment, the RTSA alert is a transient alert indication overlaid on an agent icon on a grid where the agent icon represents the agent and is displayed to a contact center supervisor. Information on the type and severity of the alert may be conveyed by text and non-text images, such as icons, colors, or symbols. A number representing a cumulative number of alert messages received for each agent may be indicated in an alert bubble overlaid on the agent icon. A viewer is able to request detailed alert data upon selecting the alert bubble.

Abstract: A method and device for automatic digital customer service agent processing to automatically redirect to a correct channel for assistance. A method includes obtaining communication information based on customer communication iterations. Customer emotion information and customer situation context information is detected based on customer information obtained from one or more devices. Redirection option information is retrieved for a condition corresponding to the customer situation context information from an assistant-redirection knowledge base. The customer situation context information, the communication information, the customer emotion information and the redirection option information are used to determine and to provide a redirection suggestion with a justification, or an answer response.

Abstract: The APPARATUSES, METHODS AND SYSTEMS FOR A CALL SEARCHER implement efficient and scalable monitoring, regulation, and allocation of communications resources within an enterprise. In one embodiment, a call searcher processor-implemented method is disclosed, comprising: obtaining an indication to perform call analytics on a communications session; recording the communications session upon obtaining the indication; analyzing via a processor the recording to determine call ratings; obtaining a call tagging rule; associating a call tag with the communications session based on the call ratings and the call tagging rule; obtaining a review request for the communications session; providing a notification of the call tag and the recording of the communications session for review upon obtaining the review request; obtaining an indication to modify the communications session in response to providing the notification; and modifying the communications session according to the obtained indication.

Abstract: A system and method for providing ongoing call center call assistance with the aid of a digital computer is provided. A call is received from a caller by an automatic call distributor in a call center and the caller is connected by the automatic call distributor to an agent of the call center. The agent's speech during the call is monitored by an intervention processor included in the call center. The intervention processor determines speech characteristics of the agent during the call, obtains predetermined speech characteristics for the agent, compares the predetermined speech characteristics to the speech characteristics determined during the call, and detects the agent being in need of assistance based on the comparison. The automatic call distributor determines a subject matter of the call and the intervention processor identifies an expert whose expertise matches the subject matter. The intervention processor patches the expert into the call.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, a voicemail device having a controller to detect a recording of a voicemail message, generate a Session Initiation Protocol (SIP) message, wherein the SIP message contains visual voicemail data associated with the recorded voicemail message, and transmit the SIP message to a cordless phone system, wherein the SIP message is received by the cordless phone system over a data port of the cordless phone system, wherein the cordless phone system comprises a base station and at least one cordless communications device, wherein the visual voicemail data is retrieved by the base station, and wherein the visual voicemail data is transmitted by the based station to the at least one cordless communications device by utilizing a cordless wireless access protocol. Other embodiments are disclosed.

Abstract: An event associated with a communication session between a first party and a second party is detected. The event is related to the communication session. For example, the event may be a phrase spoken in the communication session or a presentation of a call progression screen to a contact center agent. At this point, the communication session is analyzed for a period of non-communication that meets a defined threshold during a monitoring period associated with the event. If a period of non-communication is detected that is longer than the threshold during the monitoring period, the period of non-communication is flagged. The flagged period of non-communication can then be used to evaluate how a contact center agent is performing.