Abstract:
A computerized system for advising one communicant in electronic communication between two or more communicants has apparatus monitoring and recording interaction between the communicants, software executing from a machine-readable medium and providing analytics, the software functions including rendering speech into text, and analyzing the rendered text for topics, performing communicant verification, and detecting changes in communicant emotion. Advice is offered to the one communicant during the interaction, based on results of the analytics.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    1. Field of the Invention 
         [0002]    The present invention is in the field of telephony communications and pertains particularly to methods and apparatus for analyzing telephony interactions and reporting the results of analysis in real time. 
         [0003]    2. Discussion of the State of the Art 
         [0004]    Call centers are organizations or companies that represent one or more companies providing goods and/or services to a consumer base. Most state-of-art call centers are dual capable meaning that they may handle both switched telephony calls and data network telephony (DNT) calls. A call center typically includes a plurality of workstations comprising computers connected to a local area network (LAN) or equivalent network. Each workstation includes a telephone or equivalent for handling voice calls. Voice calls may also be handled directly n the LAN-connected computers using appropriate telephony software. 
         [0005]    Call centers are equipped generally to handle a wide range of interactions including live voice including voice over Internet protocol (VoIP), connection oriented switched telephony (COST) and messaging including email, instant messaging, and chat. Other forms of communication may also be supported like video conferencing, fax correspondence, and network-based applications for collaborating. It is important to a call center that all call center activity is recorded and made available for data mining, training, and other processes that rely on historical data for improvement of the performance of the center. Software adapted to report call center activity are typically part of a call center software suite. 
         [0006]    Existing call center reporting packages provide information on calls sorted by called party number or calling party number, and may include information gathered by an interactive voice response system. A problem with such reporting packages is that they often lack information on the content of the conversations that occurred between callers and call center agents whom are trained to handle call center interactions. Such information, if it is present at all, is in a separate set of reports and not linked to the core set of call center reports. The call center administrator thus lacks a comprehensive view the activity in the center. 
         [0007]    Another limitation in call center technology is the lack of useable interaction analytics that can be provided to agents and supervisors in real time to help them optimize the interaction experience of the customer and agent. Current call center systems do not provide speech analytic information to the agent or supervising personnel for example, but are limited to more static screen pop information that is either furnished by the caller at the start of the call or retrieved from a database during the interaction between a caller and an agent. Existing systems cannot advise the agent based on information gathered and analyzed about the current conversation. 
         [0008]    Therefore, what is clearly needed is system and methods for capturing and analyzing current interaction activity including speech and text interaction such that the outcome of analysis can be made part of the historical record of the call center and be made available to managers, supervisors, agents and systems in such a way as to enable corrective intervention to occur during the interaction process. 
       SUMMARY OF THE INVENTION 
       [0009]    A problem stated above is that it is desired in a call center environment to be able to manipulate the outcome of an interaction in progress using intelligence developed during the progress of the interaction. However, current means for acquiring the intelligence needed to determine how best to handle the interaction is limited to tapping into information already known about the caller or to information provided by the caller before or during the interaction as a result of some prompting made to the caller. 
         [0010]    While real-time behavioral analysis of the interaction process is practiced in some systems to help predict when an upsell should be offered or when an invitation to a live interaction should be provided to a customer engaged in a non-live interaction with a system or a Web site, these systems known to the inventors fall short of the ability to provide a whole analysis of the current behavioral state of the caller with respect to emotional state and topical interest of the caller that might be exhibited only during the interaction in progress with the caller or party to a non-live or live interaction. 
         [0011]    Moreover, in known systems where some intelligence is provided by analyzing browsing behavior, typed text, or voice inflection or tone, the intelligence is not developed in a sufficient timeframe to be used to manipulate the outcome of that interaction at the time of the interaction or requires human intervention to determine if a manipulation is required and what action should be pursued. 
         [0012]    The inventor therefore searched the art of call center data reporting systems, speech recognition systems, and interaction routing systems looking for elements that exhibited a propensity for integration in an automated environment. Every call in center is driven by the success of agents and automated systems relative the process of engaging and retaining customers to produce higher numbers of sales and more profitable sales. One byproduct of this activity is the existence a number of customers who have negative experiences, failed to complete transactions, or otherwise are dissatisfied with tier experiences during the interaction process. 
         [0013]    The inventors realized during an intuitive moment that if during the interactive experience, a more complete analysis of call center customer preferences and emotional state could be performed and if such intelligence gleaned could be automatically leveraged to determine appropriate actions that could influence the outcome of such interactions in a positive way through a semi-automated or wholly automated process, then higher numbers of sales and more profitable sales would result. 
         [0014]    The inventors therefore constructed a unique system for monitoring and analyzing interactions that enabled automated development of a more complete salvo of intelligence used, in some cases in automated fashion to effect an influence in the outcome of some interactions in real time that otherwise would suffer some negative result. 
         [0015]    Accordingly, in an embodiment of the present invention, a computerized system for advising one communicant in electronic communication between two or more communicants is provided, comprising apparatus monitoring and recording interaction between the communicants, software executing from a machine-readable medium and providing analytics, the software including rendering speech into text, and analyzing the rendered text for topics, performing communicant verification, and detecting changes in communicant emotion. Advice is offered to the one communicant during the interaction, based on results of the analytics. 
         [0016]    In one embodiment the electronic communication is voice communication and occurs over a telephony network integrated with a computer network and wherein the two or more communicants include a call center agent and a call center customer or customers. Also in one embodiment the electronic communication is a voice communication and the speech interaction is analyzed for speaker verification, and emotional state of one or more communicants. In another embodiment the electronic communication is a text communication and the text interaction is analyzed for communicant verification and emotional state of one or more communicants. 
         [0017]    In one embodiment the system performs emotion detection by phrase interpretation, character state interpretation and, or by emotion icon recognition. Also in one embodiment the apparatus provides call control and media processing. Further in one embodiment the advice offered is a pre-defined upsell script based on prevailing topic of the communication, the script served to one of the communicants in real time. 
         [0018]    In one embodiment the pre-defined script is selected from a pool of pre-defined scripts and served to a GUI operated by the communicant, the communicant a call center agent. Call control may be performed by a session initiation protocol (SIP) server. Also the media session markup language (MSML) may be used to control the voice platform supporting the voice communication. Further the media resource control protocol (MRCP) may be used to control the software analytics. In some cases the analytics for topic recognition may include configurable modes for hot word recognition and for continuous speech recognition. 
         [0019]    In another aspect of the invention a method for advising one communicant in electronic communication between two or more communicants is provided, the method comprising the steps of (a) monitoring and recording electronic communication between the communicants; (b) executing software from a machine-readable medium, providing analytics including rendering speech into text, analyzing the rendered text for topics, performing speaker verification, and detecting changes in speaker emotion; and (c) offering advice to the one communicant during the interaction, based on results of the analytics. 
         [0020]    In one embodiment of this method in step (a) the electronic communication is voice communication and occurs over a telephony network integrated with a computer network and wherein the two or more communicants include a call center agent and a call center customer or customers. Also in one embodiment in step (a) the electronic communication is a voice communication and in step (b) the speech interaction is analyzed for speaker verification, prevailing topics, and emotional state of one or more communicants. 
         [0021]    In some embodiments the electronic communication is a text communication and the text interaction is analyzed for communicant verification, prevailing topics, and emotional state of one or more communicants. Also in some embodiments the emotional state of the one or more communicants may be achieved by phrase interpretation, character state interpretation and, or by emotion icon recognition. In some cases in step (c) the advice offered is a pre-defined upsell script based on prevailing topic of the communication, the script served to one of the communicants in real time. In still other cases the pre-defined script is selected from a pool of pre-defined scripts and served to a GUI operated by the communicant, the communicant a call center agent. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWING FIGURES 
         [0022]      FIG. 1  is an architectural overview of a call center practicing real time interaction analysis and real time reporting of results according to an embodiment of the present invention. 
           [0023]      FIG. 2  is an architectural overview of a call center practicing caller voice analysis and script service according to an embodiment of the present invention. 
           [0024]      FIG. 3  is a block diagram illustrating basic components of a speech analysis and real time reporting system according to an embodiment of the present invention. 
           [0025]      FIG. 4  is an exemplary screen shot of an agent scripting interface according to an embodiment of the present invention. 
           [0026]      FIG. 5  is an exemplary screen shot of a graphical user interface for viewing call center activity in real time according to an embodiment of the present invention. 
           [0027]      FIG. 6  is an exemplary screen shot of a script and rules configuration interface according to an embodiment of the present invention. 
           [0028]      FIG. 7  is a process flow chart illustrating steps for analyzing voice during a call in real time and determining a script for an agent based on the results of analysis. 
           [0029]      FIG. 8  is a process flow chart illustrating steps for interaction analysis and historical reporting according to an embodiment of the present invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0030]    The inventors provide a system for monitoring and analyzing an interaction and for reporting the results of analysis of the interaction. The system incorporates one or more interaction analysis engines enabling continuous voice and text recognition with topic detection, speaker verification, and emotion detection. The system of the present invention is described in enabling detail using the following examples, which may represent more than one embodiment of the invention. 
         [0031]      FIG. 1  is an architectural overview of a call center  103  practicing real time interaction analysis and real time reporting of results according to an embodiment of the present invention. A communications network is illustrated in this example and includes call center  103 , a public switched telephone network (PSTN)  101 , and a wide area network (WAN)  102 . 
         [0032]    WAN  102  may be a corporate or private WAN including but not limiting to the Internet network. In this example WAN  102  is an Internet network and may be referred to hereinafter in this specification as Internet  102 . PSTN  101  may include wireless carriers and other telephony networks connected thereto by bridging and is meant to encompass any telephone network including digital and analog networks. The inventor chooses the Internet and PSTN as accessible networks to call center  103  because of the high public access characteristics of those networks. 
         [0033]    Call center  103  is dual capable meaning that it may receive interactions from PSTN  101  and from Internet  102 . Call center  102  has a local area network (LAN)  112  provided therein and adapted for transfer control protocol over Internet protocol (TCP/IP) among other known Internet protocols, not mentioned here but generally known to the skilled artisan. LAN  112  supports various personnel workstations as well as a host of nodes adapted to facilitate practice of the present invention. LAN  112  supports a plurality of agent workstations illustrated herein as agent workstations  113  ( 1 - n ). In this example, each agent workstation  113  ( 1 - n ) includes a LAN-connected personal computer (PC) and a telephone. Agents operating at stations  113  ( 1 - n ) are required to log into the call center system and may be located by the system using a directory server such as a directory server (DIR)  124  connected to LAN  112 . 
         [0034]    LAN  112  supports at least one manager or supervisor workstation (MGR)  116 . Workstation  116  also includes a LAN-connected PC and a telephone connected to PBX  109  by internal telephone wiring  110 . Other equipment may be included within a workstation of an agent or manager without departing from the spirit and scope of the present invention. The inventor deems that illustration of a LAN-connected PC and associated telephone is sufficient for explaining the various aspects of the present invention. 
         [0035]    In this example call center  103  has a centralized telephone switch  109  through which calls are received at the call center and placed from the call center (outbound). Switch  109  may be any type of call center switch including an automatic call distributor (ACD), a soft switch (implemented in software), or a private branch exchange (PBX). Switch  109  is a PBX in this example. Switch  109  in call center  103  has connection to a local network switch  107  by way of a telephone trunk  108 . In this example the local network switch is also a PBX switch. Callers placing telephone calls into call center  103  or receiving telephone calls from call center  103  are illustrated herein as telephone icons  104  each telephone icon representing a potential customer of call center  103 . 
         [0036]    A customer station  105  is illustrated within PSTN  101  in this example. Customer station  105  has a telephone analogous to telephones  104  connected to local switch  107  via network telephone wiring. In one embodiment cellular telephones including smart telephones are used in place of landline telephones. Customer station  105  includes a personal computer illustrated herein as connected to the Internet network directly or through an Internet service provider (ISP not illustrated). Other more direct methods of Internet access are known in the art including digital subscriber line (DSL) technology, integrated digital services network (ISDN), broadband, wireless fidelity (WiFi), cable modem, etc. 
         [0037]    All calls arriving at switch  109  in call center  103  are ultimately handled by the call center through live assistance from an agent or through the assistance of some automated system. PBX  109  is enhanced in this example by a computer telephony integrated (CTI) processor  114 , also supporting an instance of interactive voice response (IVR) unit. Processor  114  is connected to switch  109  by a CTI link  117 . Voice calls from Internet  102  and from sub-telephony networks connected to PSTN  101  may all arrive at switch  109  as incoming telephone voice calls. Agent telephones illustrated in agent stations  113  ( 1 - n ) are all connected by internal telephony wiring to PBX  109 . 
         [0038]    LAN  112  supports an Internet protocol router (IPR)  115  within call center  103 . IPR  115  is adapted to provide direct Internet access to LAN  112  in a continuous manner such as on a 24/7 basis. IPR  115  enables bi-directional data and communication flow between call center agents and systems and resources including customers connected to the Internet network. IPR  115  has connection to Internet  102 , more particularly to an Internet backbone illustrated herein as a double arrow extending through cloud  103 . The illustrated backbone logically represents all of the lines, equipment and access points that make up the Internet as a whole. Therefore there are no geographic limitations to the practice of the present invention. 
         [0039]    A chat server (CHS)  121  is illustrated within the domain of Internet  102 . CHS  121  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. CHS  121  is adapted to enable live chat sessions between agents from call center  103  and any potential customers having access to the network using a computing appliance capable of network navigation. One with skill in the art will recognize that a computing appliance capable of accessing Internet  102  may include but is not limited to a desktop computer, a laptop computer, a personal digital assistant or a smart cellular telephone. 
         [0040]    A Web server (WS)  122  is illustrated within the domain of Internet  102 . WS  122  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. Web server  122  is an electronic information server adapted to serve Web pages in hypertext transfer markup language (HTML) or another presentation protocol such as wireless application protocol (WAP). WS  122  may host one or more Web sites of one or more companies represented by call center  103 . WS  122  may be though of as a customer access point to call center  122 . One or more call center applications may be implemented in Web services description language (WDSL) or other known application protocols generally known to the skilled artisan including the inventors. A Web page served by WS  122  to any potential customer may include various options for making contact to call center  103  including voice-based, and text-based interaction through call buttons, chat options, and messaging options. 
         [0041]    Internet  102  has an email server (ES)  123  illustrated therein. ES  123  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. ES  123  is adapted to serve email to agents operating at agent workstations  113  ( 1 - n ) through IPR router  115 . In one embodiment LAN  112  supports a general email router (EMR)  125 . EMR  125  is a special email routing service for determining final internal routing to agents (over LAN  112 ) for emails sent to a generalized email address for the call center. 
         [0042]    A universal routing server (URS)  111  is illustrated within call center  103  and connected to LAN  112 . URS  111  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. URS  111  is adapted to serve internal routing strategies to requesting nodes over LAN  112 . Initial routing strategy is typically invoked through a caller pre-screening process conducted using the IVR running on CTI processor  114 . URS  111  may also be used to determine routing strategy in the case of a redirect or subsequent routing requirement as a result of interaction processing. 
         [0043]    Voice calls registered at switch  109  may be intercepted by the IVR running on CTI processor  114  to determine the purpose of the call for the benefit of selecting an internal routing destination for the call. The present invention includes a method for monitoring those calls that are routed to a live agent for the purpose of ensuring quality of the interaction and for gleaning information from the interaction in real time whereby that information is used in one or more analysis routines to provide additional data for historical reporting in one embodiment. 
         [0044]    In one embodiment of the present invention, a historical reporting server (HRS)  118  is provided within call center  103  and connected to LAN  112 . HRS  118  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. HRS  118  is adapted to record all call center activity and serving the information upon request in the form of specialized reports ordered from an interface such as a graphical user interface software (GUI SW)  127  illustrated on the computer of MGR station  116 . As was described further above in the background section of this specification, historical reporting at the time of filing this application is limited to mechanical call data such as average handling time (AHT), results of the call, and any caller information that was already known to the system or that was obtained in caller pre-processing. Information concerning the caller&#39;s mood, and topics of preference that arise during the course of the interaction and validity of the caller&#39;s identity are not available in standard reports. 
         [0045]    A call control media server (CCMS)  119  is provided within call center  103  and connected to LAN  112 . CCMS  119  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. CCMS is integration between a call control server and a media-processing server. CCMS  119  is adapted to set up and tear down the call legs of a call and the media processor is adapted to process any associated media such as voice, video, and other media applications. In this example, HRS  118  and CCMS  119  are connected together via a separate digital network. CCMS is also connected directly to CTI processor  114  via the separate data network. A call center database (CCDB)  120  is provided and is made accessible to CCMS  119  and to HRS  118 . Monitoring occurs within CCMS of all of the interactions represented therein. In one embodiment, CCMS records all data to CCDB  120  and HRS  118  serves all requested data from CCDB  120 . 
         [0046]    CCMS has at least one analytic tool  126  implemented in software (SW) that is executed at server  119  during interactions in process. Analytic tools enable performance analysis of an interaction from the perspective of the caller, the agent, or both caller and agent. In one embodiment a speech recognition system with a topic detection feature is used to determine what topics customers are talking about or are interested in based on the call transcripts. The ASR (not illustrated here) may have more than one mode of operating relative to topic detection. In one mode, the ASR system is set to recognize any hot words that are spoken by the caller. In another embodiment entire conversations are recorded and analyzed for topic detection. A version of the topic detection feature may be adapted for processing text-based interactions as well. In continuous recognition mode, the ASR recognizes the entire conversation and can generate a list of topic preferences that were prominent during the conversation. 
         [0047]    In one embodiment the system further includes an emotion detection system for determining if a caller or an agent or both is angry, disappointed, frustrated, etc. The emotion detection system (not illustrated here) may work by analyzing voice inflection, tone, volume, etc. A version of the emotion detection system may be used to analyze text message where emotion icons are used and where other emotion bearing indications are present like use of all caps in a message or other signs of mood used in a text message. 
         [0048]    In one embodiment of the present invention all of the information detected during an interaction whether the interaction is voice-based or text-based is stored with all of the traditional historical information related to the interaction and interaction initiator (customer). A manager operating GUI SW  127  from MGR station  116  can order and receive specialized historical reports that exhibit what topics the customers are talking about. The manager or supervisor can get a good indication of the levels of frustration of callers over a period of time. The information may be presented in any number of customized reports that can include information about just a single interaction to statistics relative to some of or all of the interactions that occurred and were monitored by CCMS  119 . 
         [0049]    Calls received at PBX  109  for internal routing are setup by CCMS  119  in this example after CTI notification of calls pending. CCMS may utilize IVR records of the calls to determine with the aid of URS  111  the best routing strategies for the calls being set up in the system. URS returns the routing strategy for each call based on information sent to it in the request from CCMS  119 , which includes IVR records of the pre-screening process. URS  111  may also subscribe to call center statistics on agent availability, estimated wait time (EWT) in queue, and other states before returning a viable routing strategy for each call pending. Manual routing and redirection may also be practiced by agents and supervisors logged into the system in place of or in addition to URS participation. 
         [0050]    In one embodiment the information gathered during the interactions is used to supplement historical reporting of call center activity adding new dimensions to what can be learned about the activity. In another embodiment the information gathered during the course of interaction is utilized in real time to optimize the interactive experience of the customer by providing solutions that overcome perceived states of the caller concerning mood and topical preferences. In this embodiment the invention is further characterized by provision of a real-time scripting service that may be used to send pre-defined scripts to agents engaged in a live interaction the scripts relative to information gathered during the course of the interaction. 
         [0051]      FIG. 2  is an architectural overview of a call center  203  practicing caller voice analysis and script service according to an embodiment of the present invention. A communications network  200  includes call center  203  and PSTN  101 . Internet access for call center  203  is not illustrated in this example but may be assumed present. In this example, the focus is about agent scripting as a result of analysis of information gathered during the course of live voice interactions wherein the scripts are delivered to the agents in time to influence the outcome of those interactions. 
         [0052]    Callers  104  represent customers of call center  203 , in this example. The callers access center  203  through local PBX  107  over trunk  108  and register at PBX  109  for internal routing. IVR treatment is not precluded in this example. All callers may first be treated via IVR before determining a final destination for each caller. In this example a call control server is provided separately from a media server. A session initiation protocol (SIP) server  201  is provided within call center  203  and connected to LAN  112 . SIP server  201  serves as the call control server in this example. SIP server  201  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. SIP server  201  uses SIP to set up and tear down all voice calls in this example. Other standard protocols used to set up and break down voice calls may be used in place of SIP such as Call Control extensible markup language (CCXML) for example. 
         [0053]    SIP server  201  has a separate digital network connection to an open media server (OMS)  202 . OMS  202  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. OMS  202  is adapted to perform the media processing part of the interactions set up between live agents and customers of the call center. In this example OMS  202  may be called by SIP server  201  on an as needed basis. 
         [0054]    OMS  202  includes a recording (REC) engine for recording voice interactions monitored in SIP  201 . Analytic SW tools  126  for determining topic preferences and moods or emotions exhibited by callers and perhaps agents as well are provided on OMS  202  instead of in an integrated call control/media server analogous to CCMS  119  of  FIG. 1 . A data repository labeled database  203  is provided as a centrally located and shared database for SIP server  201 , OMS server  202 , and HRS server  118 . 
         [0055]    A supervisor station  206  is illustrated in this example and may be analogous somewhat, at least in physical implementation, as MGR station  116  described with reference to  FIG. 1 . Supervisor station  206  has a GUI SW  205  provided thereon and executable there from. GUI SW  205  includes at least one enhancement over GUI SW  127 , which is the capability of allowing the supervisor to engineer agent scripts off line and to use current information about a call in progress to send particular scripts to the agent to read to the customer during the course of the interaction. 
         [0056]    In one embodiment a script server (SS)  207  is provided within call center  203  and connected to LAN  112 . SS  207  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. SS  207  is adapted to send designated pre-defined scripts to selected agents whom are in progress with a call that the script is intended to influence the outcome of. A data repository  209  labeled scripts is provided and connected to SS  207  by data link. Repository  209  is adapted to store all of the relevant scripts that can be selected and served to agents working calls. In one embodiment a supervisor or other authorized individual such as a supervisor operating station  206  has a hand in causing a script to be selected from repository  209  and served to an agent. In another embodiment scripting service is entirely automatic with the scripts being selected by a software program after analyzing results of a voice call in progress. 
         [0057]    An agent script interface (ASI)  208  is provided as a graphical user interface on each agent station such as agent station  113  ( 3 ) as illustrated in this example. Every participating agent working the live calls may be assumed to have an open instance of ASI  208  running on the display screen of their LAN-connected computers. ASI  208  is adapted to receive and display scripts sent from SS  207 . ASI  208  is not absolutely required in order to practice the present invention. A script can be engineered to execute and display on its own as an alert script that appears in a window. ASI  208  provides a more convenient and efficient way to display scripts and the scripts that are displayed may be saved and recorded along with the interaction data in the historical record of call center activity. 
         [0058]    To illustrate an example, consider a caller registered at switch  109 . The routing determination to route the call to agent  113  ( 3 ) is made after IVR pre-screening. Agent  113  ( 3 ) picks up the call and begins servicing the caller. In the meantime recording engine  204  is recording both the agent and the caller. An ASR system is turned on with topic detection and hot word recognition. An emotion detection system is turned on for the caller&#39;s voice but not for the agent&#39;s voice. During the course of the call the detection tools determine that the hot word trade was recognized and the prevailing topic is upgrading to a new system with the trade. Also during the course of the call the caller&#39;s mood or emotional state is determined to be excited or very positive. 
         [0059]    The original call may have been a service call for an existing system the caller has but with the newly detected information, a monitoring supervisor operating at supervisor station  206  aided by GUI  205  has determined that a scripting service is appropriate for the current situation with the immediate interaction being evaluated. The supervisor may highlight the caller and select an action such as “send scripting to agent of this call”. The information gathered during the call is used along with one or more rules to determine which script to send from a pool of scripts. The decision to select and send a specific script to a particular agent involved in a call is made automatically once the supervisor invokes the service on behalf of a call in progress. 
         [0060]    SS  207  selects the correct script based on information in hand and rules governing which script to send based on that information. In this case SS  207  selects a script from scripts database  209  and serves it to ASI  208  open on the PC display screen. The script may appear with a system prompt urging the agent to read the script to the customer. In this use case the script may be an offer to “upgrade” to the next best system and to accept the “trade” offered by the customer. In this case emotion detection determined that the caller was excited reinforcing the idea of intervening with an up-sell script. In this embodiment all of the activity including the caller and agent voice recordings, transcripts, and the topic prevalence, and the emotional state of the caller and/or agent is recorded in the historical record of activity at the call center and is subject to inclusion in one or more custom reports ordered by a manger or supervisor. 
         [0061]    In this embodiment scripting may be ordered for any agent that is currently involved in a current interaction. Selection of scripts is dependant in part on what emotional state exists with the caller and what topics are prevailing in the conversation. In one embodiment the same topic and emotion detection schemes can be used to influence a live chat or an instant message session. In one embodiment Web visitors can be offered services base on analysis of the Web behavior that can be linked to topic prevalence or to an emotional state. For example, a topic can be detected based on the visitor&#39;s page preference or click-history at the Web site. The emotional state of the visitor might be deduced by observing the navigation behavior, for example going back and forth repeated on the same sequence of Web pages could indicate frustration. 
         [0062]      FIG. 3  is a block diagram illustrating basic components of a speech analysis and real time reporting system according to an embodiment of the present invention. Open Media Server (OMS)  202  from  FIG. 2  is illustrated in this example in more detail. Components of analytic tools  126  of  FIGS. 1 and 2  are in one embodiment hosted on OMS  202 . In another embodiment they may be hosted within the call control server such as SIP server  201  described in  FIG. 2 . 
         [0063]    An automated speech recognition (ASR) system  308  is provided in this example and has two separate modes of speech recognition. ASR system  308  has a hot word recognition mode (HWRM) and a continuous speech recognition mode (CSRM). ASR system  308  has a connection to an ASR library repository  305  adapted to store vocabulary and other data required to enable ASR function. In this embodiment ASR system runs on OMS  202 , which is connected by a data link  314  to a monitoring CTI processor and therefore has access to the live voices of the agent and the customer of any particular call being monitored. 
         [0064]    Output from ASR system  308  may be recorded by a call recording system illustrated herein as a call recording system  315 . Output from ASR system  308  may be processed for topic detection by a topic detection system (SYS)  310 . Topic detection system  310  may be turned on or off in a pre-configuration process. With topic detection turned on, the system attempt to determine if one or more high priority topics are prevalent in the conversation between an agent and a customer of a voice call. Topic detection system  310  may parse transcripts of the conversation to detect topics that are primary in the conversation. 
         [0065]    Output from ASR system  308  may be processed for emotion detection by an emotion detection system (SYS) illustrated herein as an emotion detection system  309 . Emotion detection system may work in conjunction with speech recognition to detect if any prevalent emotional states can be detected in either the customer&#39;s voice patterns or in the agent&#39;s voice patterns, or both. Emotional detection system  309  may analyze voice inflection, tone, volume, pattern and other voice characteristics to determine if any significant emotional state can be implied to the customer, to the agent, or to both the customer and the agent during a conversation. Emotional detection SYS  309  may be turned on or off during a pre-configuration process. 
         [0066]    Output from ASR system  308  may be processed by a speaker verification system  311 . Speaker verification system may detect if there are delays or inconsistent answers to specific questions typically asked of callers to verify that the caller is who they say they are. If a caller delays or fails to answer one or more of these types of security questions, the speaker verification system may generate an alert and send the alert to the agent and/or supervisor to alert them of a possibility of fraud. Speaker verification system  311  can be turned on or off during a pre-configuration process. In one embodiment speaker verification system  311  has access to a repository containing speaker verification data such as answers to security questions that are kept on file. In one embodiment speaker verification system  311  may also have access to a third party validation system that may provide some validation service for callers. In one embodiment voice patterns of repeat callers are recorded and saved. In this embodiment the speaker verification system may compare a callers voice against a sample of the caller&#39;s voice kept on file for the purpose. 
         [0067]    In one embodiment ASR system  308  is capable of receiving and delivering routing instructions to an agent engaged in a conversation in a case where some analysis of a customer&#39;s speech warrants additional routing to another party, for example, to diffuse a crisis or to help pacify a disgruntled customer. In this case ASR system  308  may have connection to a universal routing server (URS)  306 . URS  306  is analogous to URS  111  described further above with reference to  FIG. 1 . 
         [0068]    In this example, OMS  202  includes an interaction queue  307  that is adapted to represent current interactions being processed by the system of the invention including an indication of which parties to each conversation are being analyzed by one or more of the analytic processes. In a visual representation of queue  307  each conversation has two parties listed, an agent (row labeled A) and a customer (row labeled C). Reading from left to right, a first interaction represented in queue indicates that the customer will be analyzed but the agent will not. The second and third conversation queued indicate that both parties to the conversations will be analyzed. The pattern follows for every column representing a two party conversation. In one embodiment the queue representation may be extended for three party calls and conference calls where some of the participants may be analyzed and some may not. 
         [0069]    The granularity of configuration for agents may come down to each agent for configuring if and what analysis routines will be performed on that agent&#39;s voice when in conversation with a customer. In most embodiments all customers calling in have their speech processed for emotion and topic prevalence. However, customers may be configured individually as well. For example, a rule could be created for John Doe to always analyze his voice for emotional state when he calls in. It may be a fact that John is easily upset and often expresses disappointment or anger even though he may be a great customer. In one embodiment queue  307  contains current interactions in progress where an agent and a customer are actively engaged. In another embodiment queue  307  contains interactions that are still pending but where the agent that will take the call has already been selected by the routing server. 
         [0070]    Output from call recording SYS  315  is sent to a real time reporting server (RTRS)  301 . RTRS  301  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. RTRS  301  is analogous to HRS  118  described previously with reference to  FIG. 1 . RTRS is connected to historical database  112  introduced and described previously with reference to  FIG. 1 . All recordings made of conversations are saved as well as transcripts of the conversations and other media processed with those conversations. 
         [0071]    In one embodiment where it is desired to influence the outcome of a conversation, output from emotion detection system  309  and from topic detection system  310  is input into a speech analysis recommendation engine (SARS)  302 . SARS  302  is adapted to take the results of emotion detection system  309  and the results of topic detection system  310  and process those results using one or more algorithms to determine an appropriate course of action given the results of speech analysis. SARS  302  has a digital medium accessible thereto for storing and serving data and for storing and executing applications enabling server function. 
         [0072]    SARS  302  may be connected to a rules base (not illustrated) containing rules pertinent to what courses of action should be taken based on what input parameters. One course of action is a rerouting of the caller to a new destination. Another course of action is serving a notice to agents containing suggested scripting for the agent to read to the customer. Any negative indication found through agent voice processing may result in a disciplinary recommendation, a temporary re-assignment, a simple warning, or a request to attend a specific training session, or the like. SARS is, in one embodiment connected directly to RTRS  301  via a data link. In this case SARS  302  sends its output to RTRS  301  for historical data storage and for real time reporting. 
         [0073]    In one embodiment SARS  302  may have a LAN connection for the purpose of communication directly with agent stations and supervisor stations. However in this embodiment SARS  302  only reports to RTRS  301 . RTRS  301  is adapted to server data relative to current conversations to GUI  205  running in this example on the computer of a supervisor workstation  304 . It is noted herein that voice analysis data and recommendation data may also be made part of the historical record of call center activity. 
         [0074]    Data served from RTRS  301  to GUI  205  for display may be packaged in the form of one or more custom reports  313 . In one embodiment a supervisor subscribes to RTRS  301  and may pre-configure rules relative to what solutions may be recommended by SARS  302 . The supervisor may also pre-configure the types of reports that are desired and for who in the group including customers and agents engaged in conversation the reports will be about. For example, a supervisor may order a report that reveals a real time percentage of the total number of current customers engaged in monitored conversation that have had a negative emotions rating during their conversation. 
         [0075]    In one embodiment of the invention, a supervisor working at supervisor station  304  may select and serve scripts to agents based on real time information about their current conversations with customers. Agent workstation  303  includes agent-scripting interface (ASI)  208  and is adapted to receive scripting sent by a system or by a supervisor or manager. RTRS  301  may send a report to the supervisor of workstation  304 , the report displaying in GUI  205 . The report may alert the supervisor to favorable topical preferences in some of the current conversations in progress. The report may include a list of one or more than one recommended script (recommended by SARS  302 ). When SRARS  302  makes a recommendation, that recommendation is almost immediately available to a supervising entity through push alert or through receipt of a custom report that contains the recommendation. In one embodiment GUI  205  includes a real time activity panel that when displayed lists all of the current interactions being monitored, identifies the parties to those interactions, and displays any real time analytic results fleshed out during those interactions such as current emotional states and topic prevalence states. 
         [0076]      FIG. 4  is an exemplary screen shot  400  included in an agent-scripting interface according to an embodiment of the present invention. Screen shot  400  represents a system recommendation that includes scripting service to an agent that is currently interacting with a customer. Screen shot  400  includes a title bar  401  that identifies the screen as a call recommendation. Screen shot  400  may be referred to hereinafter as a call recommendation screen  400 . Title bar  401  of call recommendation screen  400  is personalized to a call center agent John who is the recipient of the recommendation. Bar  401  identifies the caller currently in interaction with agent John as Mr. Smith. The title bar also indicates the time in for the current interaction, in this case 1:20 seconds meaning that John has been on the telephone with Mr. Smith for one minute and 20 seconds. The time status feature on the title bar increments accordingly as the call progresses. A link between the ASI and the call control server enables the stopwatch feature for every conversation. 
         [0077]    In one embodiment a caller identification number  402  is displayed in the call recommendation, which could be the Mr. Smith&#39;s telephone number. Real time analytic results  403  may be displayed in the call recommendation screen. In this case a hot topic or hot word is “System Upgrade”. Therefore, the customer has mentioned or asked about a system upgrade either directly or casually during the interaction. The call recommendation screen may include a prompt  404  intended for John. Prompt  404  simply asks John to read the closing script  405 . The system has already determined that the call will be routed to another more-experienced agent so John must end the conversation until a new agent picks up the call. In one embodiment the script displays for reading and becomes part of the interaction history between John and the customer Mr. Smith. The script simply informs Mr. Smith that he will be routed to another agent Ben that will help him with upgrading his current system. Agent John will likely hold to make sure that the other agent is in place to accept the call. 
         [0078]    A system prompt or command  407  is displayed beneath closing script  405  to transfer the caller to Ben Leech ID #30124. The system has already determined that Ben Leech is the best possible match for the caller at the current time. Call recommendation  400  includes transfer options  406  of automatic transfer (system performed) or manual transfer (agent task). While agent John is still on the telephone with Mr. Smith with the transfer in progress, Ben Leech picks up the call and reads an introductory script  408  sent to his ASI and to the ASI of John. 
         [0079]    In one embodiment script  408  is not a pre-defined script and may be an actual text rendition of what Ben says when he picks up the telephone with John and Mr. Smith on the line. After the greeting from Ben, a system prompt  409  appears on call recommendation  400  asking John to please hang up the telephone and take the next call. A script server may serve call recommendation  400 , or it may be served by a speech analysis recommendation system (SARS) analogous to SARS  302  of  FIG. 3 , or by a supervisor operating a supervisor station like station  304  of  FIG. 3 . In another embodiment the script appears in the call recommendation window, which is generic to the agent-scripting interface. In this case both scripts and system prompts may appear as required in the interface using the screen as a template the data appearing in the appropriate fields. 
         [0080]      FIG. 5  is an exemplary screen shot  500  of a graphical user interface for viewing call center activity in real time according to an embodiment of the present invention. Screen shot  500  represents a current call center activity view or report that may be ordered by or pushed to a supervisor in charge of a particular group of agents. This view may be served to the supervisor GUI analogous to GUI  205  described previously. View  500  has a title bar that includes the title CC Activity View [Real Time]. The title bar also has the current time and date. The view is personalized to a Mr. Blake, which is the recipient of the view. 
         [0081]    View  500  may include a window dedicated to the display of group statistics  501  as they are at view time. In this case Mr. Blake is a supervisor in charge of a campaign utilizing a specific group of call center agents. Reading from top down the data reveals an Agent Group assigned to and scheduled to work the campaign. The Agent Group=Group (C) [System Sales]. In this case the type of campaign is an outbound calling campaign. The campaign duration=6 hours. There are a total of 22 agents working the campaign. An interactive option [List} may enable the supervisor to call up a detailed interactive list of those agents. 
         [0082]    Real time statistics indicate that there are 19 calls in the queue and 8 calls in progress, meaning 8 calls are currently being monitored and processed for information using the voice analytic tools described above. The estimated wait time (EWT) in queue is 4 minutes while the average handling time (AHT) for a call is 3 minutes. The current closing rate is 56% meaning 56% of the total number of calls resulted in a sale. 
         [0083]    View  500  includes emotion detection system [ED-SYS Data]  502  for the group of interactions that are currently in progress. Of the 8 calls in progress, there are 2 calls where the caller is angry. A telephone icon displays each call having an angry caller and an indication of how long the call has been in progress. The freshest call with an angry caller is just 1.00 minute old. The next call with an angry caller is 2 minutes and 43 seconds old. With an average handling time of 3 minutes, the supervisor may elect to intervene only on the freshest call at 1:00 minute. Each of the call icons is interactive and can be manipulated to call up all of the information about the call, the caller, and the agent. An interactive option labeled Send Script is provided to the right of each troubled conversation. A supervisor may click on the option to call up a manual script selection interface. The supervisor may first highlight the conversation that she wants to influence and then may browse for or select a script from a list or pool of pre-defined scripts. Once the script is selected, hitting send automatically causes the script to be sent to the ASI of the agent in that conversation. 
         [0084]    Also listed in parameters  502  is the total number of calls in the group of 8 calls in progress where the agent is angry. In this example only 1 call is in progress where the ED SYS has detected anger in the agent. A telephone icon represents that call. Next to the icon an indication is provided of the current age of the call, in this case 2 minutes and 10 seconds. A script or other intervention may be warranted for that call. Another set of real-time parameters  503  is provided below the ED-SYS Data. These data are Topic Detection system data [TD-SYS Data]. Of the 8 calls in progress, 5 of those have hot topics detected that are prevalent in the conversation. The 5 calls are listed in order from freshest call to the oldest call. In one embodiment the supervisor may mouse over any one of the displayed call icons to get the most prevalent topic of that call. The hot topic for the oldest call on the list is “Upgrade”. Some conversations may be listed in more than one data set. On conversation may have a hot topic detected, an angry caller detected and an angry agent detected. 
         [0085]    Caller verification alert bar  506  informs the supervisor of how many of the current conversations have callers who are suspect of fraud. In this example the number is 0 calls. This number should typically remain at 0 or very low with good security practices. A set of interactive options  505  is provided in view  500  beneath the standard parameters. For example, an option to add or subtract agents from the group (C) is presented. A supervisor may also be able to transfer agents from one group, say group C to another group say group D. A next interactive option allows a supervisor to perform a manual rerouting of a caller from one agent to another agent. This process may also be wholly automated using a script server. A next option enables the supervisor to send an up sell script to any agent involved in conversations. 
         [0086]    View  500  has some pre-configuration options  504  that a supervisor may set prior to running a call campaign. A first option is let the system determine the best actions to pursue in the face of caller anger, top topic, agent anger, etc. In this case all of the routing and call transfer steps are automated. Another option is prompt me and ask me what to do. In this case the system only take corrective action at the bidding of the supervisor. The last option enables the supervisor to initiate all of the actions. In this case the supervisor selects and serves scripts and performs rerouting from the desktop. In a case where there may be hundreds of active calls automation may be the best rule whereas for small groups a human operator may manage the calls in progress. 
         [0087]      FIG. 6  is an exemplary screen shot of a script and rules configuration interface  600  according to an embodiment of the present invention. Configuration interface  600  may be a static part of the supervisor GUI for receiving reports. The interface has a title bar defining the window as a Script Configuration Interface. Interface  600  enables an agent to configure rules and to write scripts that may be selected for scripting service to agents in the field. The interface includes a visual list of available topics to write scripts about. The available topics are hot words that if spoken by a caller could cause the system to recommend a script. In interactive option  602  is provided to enable the supervisor to add or remove topical hot words. The hot words would be recognized during automated speech recognition performed by the ASR system. Hot words may also be parsed from text-based interactions in some embodiment of the present invention. 
         [0088]    Script configuration interface  600  includes access to available scripts that have been pre-configured and stored in a repository analogous to the script repository  209  described with reference to  FIG. 2 . In this example, the supervisor has access to five available up sell scripts, two available pacification scripts, and two available transition scripts. An up sell script is an offer to upgrade or to purchase a higher priced product or product version. A pacification script might be used to calm an angry customer. A transition script is used to inform a customer that he or she will be redirected to a different agent to finish the transaction. 
         [0089]    An interactive option  604  is provided within interface  600  to enable creating and adding new scripts to the pool of existing scripts. An interactive option  605  is provided that enables a supervisor to add or edit existing scripts. An interactive option  606  is provided that enables the supervisor to delete existing scripts from the pool of scripts. Scripts are selected by rule based on results of analysis of customer and/or agent behavior, topic detection and emotion detection. A speech analysis recommendation engine (SARS) described further above may be responsible for processing those results before a recommendation is made. A recommendation to script an agent may be passed to the supervisor interface (GUI  205 ) and the supervisor may have the last decision of whether to send a recommended script or to send a different script or no script. In one embodiment script selection and service is completely automated and occurs in the background without human input. 
         [0090]    Interface  600  includes a rules configuration pane  608 . There are several interactive options made available to a supervisor through rules configuration pane  608 . An interactive option is provided that enables the supervisor to create a new rule. An interactive option is provided that enables the supervisor to edit an existing rule. A rule created to help decide whether to recommend a script or not depends on certain conditions that are inferred through voice analysis and text analysis (live text interaction). An interactive option is provided within rules configuration pane that allows the supervisor to view and edit existing conditions that might lead to rule application and subsequent selection of one or more scripts. In one embodiment more than one script might be recommended whereby the supervisor picks one of the list to send to a customer. 
         [0091]    Configuration pane  608  also contains an interactive option for specifying new conditions for triggering rules. The exact conditions specified will depend on the nature of the campaign. An interactive option is provided within rules configuration pane for linking new rules to existing or newly created scripts. Interaction with any of the described options in configuration pane  608  may bring up new windows to facilitate the tasks specified by the option. An interactive option for saving and submitting a particular configuration of rules and scripts is provided as well as a link that enables testing a new configuration to determine if the results and rules applied in a situation lead to recommendation of the appropriate scripts or script. 
         [0092]      FIG. 7  is a process flow chart illustrating steps  700  for analyzing voice during a call in real time and determining a script for an agent based on the results of analysis. At step  701  a participating agent picks up a call from queue. The call may have been previously processed by IVR to determine internal routing strategy. At step  702  the system turns on the ASR system for the call. The call may or may not be recorded by default. In one embodiment all calls are recorded. In one embodiment the call recording system is turned on for each call that the system determines should be recorded. 
         [0093]    At step  702  the system may select an ADR mode such as continuous voice recognition or hot word recognition. A feature of the ASR system for recognizing topics may be turned on or off by default. Typically topic detection is on by default for the purpose of generating system recommendations. The system may turn on the caller verification system at step  703 . In one embodiment step  703  occurs only after the ASR system recognizes one or more security questions asked of the caller by the agent. The system may turn on the emotion detection system at step  704 . 
         [0094]    All of the features of the ASR system including topic and emotion detection may be run for the caller&#39;s voice only or for both the caller and the agent. In one embodiment certain agents will be monitored while certain other agents in the group may not be monitored. Typically all callers would be monitored but it is possible to selectively monitor calls while other calls are not monitored. At step  705  the system attempts to verify the callers identity. In one embodiment the ASR system recognizes a security question and then listens with emotion detection and topic detection turned on to determine if the question is answered correctly and if so was it an uncomfortable answer for the caller. For example, is the security question was “What is your date of birth” and the caller has a hard time responding even though the right answer is given, the system may make a determination whether the caller is who the caller claims to be at step  706 . 
         [0095]    If the caller verification system determines that the caller identification cannot be confirmed, then at step  707  the call may be terminated and a fraud alert may be sent to the managing supervisor at step  708 . There may be several differing schemes for verifying the identity of a caller including matching voice pattern of the caller with a voice pattern of the caller that is kept on file at the call center. Generally if the caller successfully answers one or more security questions without much hesitation the caller ID is confirmed. The system of the invention is compatible with most security regimens such as are used by financial institutions and the like. 
         [0096]    If the caller verification system confirms the identity of the caller at step  706 , then as the call is being handled, the system checks if any prevalent topics can be discerned for the ensuing conversation at the current time in step  709 . If no hot words or topics are identified by the system in step  709 , the system may determine subsequently or at the same moment if there is any significant emotional state detected in the conversation. For example, the caller may become frustrated or the agent may become frustrated or crass. If no topics could be verified and no adverse emotional states are detected, then the process may skip to step  714  where the agent finishes the call without any outside influence. 
         [0097]    It is noted herein that the steps of topic and emotion detection may be continually running during the life of the conversation and either system will take action if triggered by topic recognition or by the recognition of an emotional state or by both. It is also noted that detection of a prevalent topic or topics in a conversation may be confirmed while no significant emotional state can be determined. Likewise, an emotional state may be determined without topic recognition being successful for a conversation. 
         [0098]    At step  709  if the system detects a prevalent topic for the conversation, the system classifies the topic and at step  710  and may also select a script for the agent to read at step  711 . In one embodiment if a topic is detected that might lead to script service to the agent, the system waits until the emotional state of the caller and/or agent is confirmed if any. In one embodiment a topic may be detected and a script selected based on the topic but before a script is sent, the emotion detection system determines that the caller is angry. A script for an angry caller may be more important than a script offering an up sell to the caller and therefore may take priority in any given conversation. After step  709  regardless of whether a topic was found or not, the system moves to step  712  for emotion detection unless that feature is purposely turned off for the call. 
         [0099]    If topic prevalence for the conversation is determined at step  709  then at step  710  the topic is classified and the agent of the call is notified to receive a script at step  711  as part of the system recommendation described further above with reference to  FIG. 3 . If the topic detection system confirms a topic the system will still check for emotional states of the caller at step  712 . At step  712  if emotion is not detected and no topic is detected at step  709 , then the process may skip to step  714  where the agent finishes the call as mentioned above. 
         [0100]    If a significant emotional state is detected in the conversation at step  712  the system may classify the emotion and may select a script for the agent at step  713 . If an emotional state is detected and classified, the system may wait to see if a topic could be detected. For example, the emotional state detected in the caller&#39;s voice may be one of excitement and the topic that is prevalent might be “new system”, in which case the script triggered by the topic, perhaps and up sell script, is validated as well be the emotional state of the caller. 
         [0101]    If two different scripts are selected for an agent in a conversation, one relative to topic and one relative to emotion, the system may enable the agent to make a choice of which script to actually read to the caller. In one embodiment the supervisor may make the final decision over which of two widely variant scripts will be read to the caller. In still another embodiment, an automated routing may weigh the selected scripts against all of the rules and make a determination of which script is most important like a tiebreaker routine. Obviously an angry caller would not be a good candidate to be read an up sell script based on a prevalent topic. Emotional states may range from anger, frustration, confusion, and melancholy to happy, excited, and ecstatic. 
         [0102]    After the recommended script is sent to the agent at step  711 , ultimately the system will save all of the call data including all of the results in a historical database for reporting. It is noted that real time reporting may include reporting of both real time information or states and static information that is the same every report like standard customer data. In one aspect a supervisor may screen a custom report to see only the real-time data. In one embodiment a supervisor may elect to physically monitor all connected conversations from a dashboard style interface such as may be accessed using GUI  127  or GUI  205 . In this case the supervisor may choose which calls to monitor and which calls to let go. In one aspect the supervisor may configure topic detection and emotion detection to automatically turn on for a conversation that exceeds the AHT for a call or some other time limit imposed on the conversation. There are many possibilities. 
         [0103]      FIG. 8  is a process flow chart illustrating steps  800  for interaction analysis and historical reporting according to an embodiment of the present invention. At step  801  the system selects an interaction to process. Typically, in an open media queue the interaction may be a voice-based interaction (call) or a text-based interaction request (Chat, IM). At step  802  the system determines if the interaction is a voice interaction or a text interaction. At step  802 if the interaction is a voice interaction then the system turn on the ASR system with topic recognition at step  804 . The system also turns on the caller verification system at step  806  and the emotion detection system at step  807 . 
         [0104]    If the interaction of step  801  is determined a text interaction at step  802  then the process moves to a process branch beginning with step  803  for turning on a text recognition system with topic detection. Then the system turn on a text-based emotion detection system, which looks for hints of emotional state within the typed text of a text interaction. 
         [0105]    For the voice-based branch of process steps  800  the system attempts to verify the ID of the caller at step  811 . At step  813  the caller verification systems decides if the caller is authentic. If the caller is judged not to be authentic at step  811 , then the process moves to step  815  where the call may be terminated. In that case a notice of fraud may be sent to the managing supervisor in charge of the agent group at step  817 . If the caller is determined to be authentic at step  813  then the call is monitored for topic and emotion detection and the outputs of those systems may be combined and aggregated for the call at step  808 . 
         [0106]    For the text-based branch of process  800  the outputs of the text-based versions of the topic detection and emotion detection systems are combined and aggregated for the text interaction at step  808 . At step  809  all of the interaction data and results of voice/text analysis are stored in the historical database managed by a real time reporting tool or server analogous to server  301  of  FIG. 3 . At step  810 , the reporting server may serve the interaction data including results of analysis along with standard data to an authorized requester such as a managing supervisor. Each interaction in progress may be viewed in real time through a GUI dashboard style interface for both text-based and voice-based interactions. In one embodiment the supervisor or manager may select and send scripts to agents in real time based on analytic results whether the interaction is a voice call, a chat session or an instant message session in progress. Moreover, the historical record is supplemented with group statistics about topic preference and emotional states of interaction participants. These stats may be mined for useful information that may aid in refining scripts, processes, voice applications, and other call center processes and objects. 
         [0107]    It will be apparent to one with skill in the art that the interaction participant monitoring and reporting system of the invention may be provided using some or all of the mentioned features and components without departing from the spirit and scope of the present invention. It will also be apparent to the skilled artisan that the embodiments described above are specific examples of a single broader invention which may have greater scope than any of the singular descriptions taught. There may be many alterations made in the descriptions without departing from the spirit and scope of the present invention.