Abstract: Methods, apparatus, and systems for analyzing data trends are described herein. The present disclosure includes the identification of trending terms in data through the use of an unsupervised algorithm. Trending terms are identified and counted during a first and second time period without reference to a library of pre-defined terms, along with at least one reason for using such trending terms. The set of trending terms and the at least one reason for use of the trending terms are displayed to a user.

Abstract: The methods, apparatus, and systems described herein are designed to reduce false positive voice print matching with fraudulent callers. A voice print of a call is created and compared to known voice prints to determine if it matches one or more of the known voice prints, and to transaction data associated with a database of voice prints. The methods include a pre-processing step to separate speech from non-speech, selecting a number of elements that affect the voice print the most, and/or generating a first score based on the number of selected audio elements matching audio elements of a voice print from the plurality of fraudulent speakers, determining if the first score exceeds a predetermined threshold score for the fraudulent speaker, and comparing the selected audio elements for the unknown caller, where the score exceeds the predetermined threshold score, to the voice prints associated with the customer account.

Abstract: The methods, apparatus, non-transitory computer readable media, and systems described herein include recording a mono recording of a software and a customer inquiry communication using a microphone to interpret and respond to the customer inquiry communication, wherein the mono recording is unseparated and includes customer voice data and audio data generated by the software agent, separately and concurrently recording the software agent audio data in an agent recording, and subtracting agent audio data from the unseparated mono recording to provide a separated recording including only customer voice data.

Abstract: The methods, apparatus, and systems described herein facilitate decision-making by providing predictions of outcomes and behaviors. The methods include receiving a communication between an agent and a prospect, analyzing density of keywords in a text version of the communication to determine the type of communication and amount of value time, determining if the communication is a first meaningful contact based on the type of communication and amount of value time, and predicting a likelihood of a prospect's action based on the determination.

Abstract: The methods, apparatus, and systems described herein facilitate instructor decision-making based on an analysis of communication(s) between an instructor and a student, including to provide predictions of student outcomes. The methods include receiving communication(s) posted by a student, detecting personality types along with keywords and phrases used by the student and the instructor with a psychologically-based linguistic analysis of the communication(s), scoring the student and instructor communications based on the detected keywords and phrases compared to a library of keywords and phrases, aggregating the student scores by personality type and instructor, correlating the student and instructor scores with historical student data, creating an evaluation report to provide guidance to the students for enrollment based on the correlated scores, and displaying the evaluation report on a student device.

Abstract: Methods, behavioral assessment computer program products, and systems for analyzing electronic customer communication data, generating behavioral assessment data and displaying instructions to a user that include receiving electronic customer communication data from one or more servers configured to provide a user interface comprising a web site, web portal, or virtual portal or application, wherein the electronic communication data includes comments posted on an online forum; determining that the comments include bot comments; identifying a customer associated with the received electronic customer communication data; generating behavioral assessment data for the received electronic customer communication data for the identified customer; and displaying instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data.

Abstract: A method for analyzing caller interaction events that includes receiving, by a processor, a caller interaction event between an agent and a caller, extracting, by a processor, caller event data from the caller interaction event, analyzing, by a processor, the caller event data, and generating, by a processor, a report displaying one or more selected categories of the caller event data. Systems and non-transitory, computer readable media that control an executable computer readable program code embodied therein, are also described.

Abstract: Methods, behavioral assessment computer program products, and systems for analyzing electronic customer communication data, generating behavioral assessment data and displaying instructions to a user that include receiving electronic customer communication data from one or more servers configured to provide a user interface comprising a web site, web portal, or virtual portal or application, wherein the electronic communication data includes comments posted on an online forum; determining that the comments include bot comments; identifying a customer associated with the received electronic customer communication data; generating behavioral assessment data for the received electronic customer communication data for the identified customer; and displaying instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data.

Abstract: A method for analyzing caller interaction events that includes receiving, by a processor, a caller interaction event between an agent and a caller, extracting, by a processor, caller event data from the caller interaction event, analyzing, by a processor, the caller event data, and generating, by a processor, a report displaying one or more selected categories of the caller event data. Systems and non-transitory, computer readable media that control an executable computer readable program code embodied therein, are also described.

Abstract: The methods, apparatus, non-transitory computer readable media, and systems described herein include recording a mono recording of a software and a customer inquiry communication using a microphone to interpret and respond to the customer inquiry communication, wherein the mono recording is unseparated and includes customer voice data and audio data generated by the software agent, separately and concurrently recording the software agent audio data in an agent recording, and subtracting agent audio data from the unseparated mono recording to provide a separated recording including only customer voice data.

Abstract: Methods, behavioral assessment computer program products, and systems for analyzing electronic customer communication data, generating behavioral assessment data and displaying instructions to a user that include receiving a plurality of types of electronic customer communication data by one or more servers configured to provide a user interface including a web site, web portal, or virtual portal or application, wherein at least one of the types of electronic communication data includes voice data, generating a text file from the voice data, identifying a customer associated with the electronic communication data received by the one or more servers, generating behavioral assessment data for the electronic communication data for that identified customer by analyzing the customer's electronic communication data, and displaying instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data, and wherein the user includes the identified customer or a c

Abstract: The methods, apparatus, and systems described herein are designed to reduce false positive voice print matching with fraudulent callers. A voice print of a call is created and compared to known voice prints to determine if it matches one or more of the known voice prints, and to transaction data associated with a database of voice prints. The methods include a pre-processing step to separate speech from non-speech, selecting a number of elements that affect the voice print the most, and/or generating a first score based on the number of selected audio elements matching audio elements of a voice print from the plurality of fraudulent speakers, determining if the first score exceeds a predetermined threshold score for the fraudulent speaker, and comparing the selected audio elements for the unknown caller, where the score exceeds the predetermined threshold score, to the voice prints associated with the customer account.

Abstract: Methods, apparatus, and systems for analyzing data trends are described herein. The present disclosure includes the identification of trending terms in data through the use of an unsupervised algorithm. Trending terms are identified and counted during a first and second time period without reference to a library of pre-defined terms, along with at least one reason for using such trending terms. The set of trending terms and the at least one reason for use of the trending terms are displayed to a user.

Abstract: The methods, apparatus, and systems described herein facilitate instructor decision-making based on an analysis of communication(s) between an instructor and a student, including to provide predictions of student outcomes. The methods include receiving communication(s) posted by a student, detecting personality types along with keywords and phrases used by the student and the instructor with a psychologically-based linguistic analysis of the communication(s), scoring the student and instructor communications based on the detected keywords and phrases compared to a library of keywords and phrases, aggregating the student scores by personality type and instructor, correlating the student and instructor scores with historical student data, creating an evaluation report to provide guidance to the students for enrollment based on the correlated scores, and displaying the evaluation report on a student device.

Abstract: The methods, apparatus, non-transitory computer readable media, and systems described herein include recording a mono recording of a face-to-face communication between an agent and a customer using a microphone, wherein the mono recording is unseparated and includes agent voice data and customer voice data, separately recording the agent voice data in an agent recording using a second microphone; aligning the unseparated mono recording and the agent recording so they are time-synched; subtracting agent voice data from the unseparated mono recording using the agent recording to provide a separated recording including only customer voice data, wherein the agent voice data is subtracted from the unseparated mono recording based on the alignment, sound frequency analysis, or both; converting at least the customer voice data to text; and determining a personality type of the customer by applying one or more computer-implemented linguistic algorithms to the text of the customer voice data.

Abstract: The methods, apparatus, and systems described herein are designed to identify fraudulent callers. A voice print of a call is created and compared to known voice prints to determine if it matches one or more of the known voice prints. The methods include a pre-processing step to separate speech from non-speech, selecting a number of elements that affect the voice print the most, and/or computing an adjustment factor based on the scores of each received voice print against known voice prints.

Abstract: The methods, apparatus, and systems described herein are designed to identify fraudulent callers. A voice print of a call is created and compared to known voice prints to determine if it matches one or more of the known voice prints, and to transaction data associated with a database of voice prints. The methods include a pre-processing step to separate speech from non-speech, selecting a number of elements that affect the voice print the most, and/or computing an adjustment factor based on the scores of each received voice print against known voice prints.

Abstract: The methods, apparatus, and systems described herein facilitate decision-making by providing predictions of student outcomes and behaviors. The methods include receiving a communication posted by a student, identifying keywords in text of the communication associated with one or more student metrics, scoring the communication for at least one student metric, and predicting a likelihood of a student outcome based on the score.

Abstract: Methods, apparatus, and systems for analyzing data trends are described herein. The present disclosure includes the identification of trending terms in data through the use of an unsupervised algorithm. Trends are identified and counted during a first and second time period. The frequency and co-occurrence of groups of terms is compared to determine a set of trending terms without reference to a library of pre-defined terms. The set of trending terms is displayed to a user.

Abstract: Methods, behavioral assessment computer program products, and systems for analyzing electronic customer communication data, generating behavioral assessment data and displaying instructions to a user that include receiving a plurality of types of electronic customer communication data by one or more servers configured to provide a user interface including a web site, web portal, or virtual portal or application, wherein at least one of the types of electronic communication data includes voice data, generating a text file from the voice data, identifying a customer associated with the electronic communication data received by the one or more servers, generating behavioral assessment data for the electronic communication data for that identified customer by analyzing the customer's electronic communication data, and displaying instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data, and wherein the user includes the identified customer or a c