Abstract:
A speaker identification system (“system”) automatically assigns a speaker to voiced segments in a conversation, without requiring any previously recorded voice sample or any other action by the speaker. The system enables unsupervised learning of speakers' fingerprints and using such fingerprints for identifying a speaker in a recording of a conversation. The system identifies one or more speakers, e.g., representatives of an organization, who are in conversation with other speakers, e.g., customers of the organization. The system processes recordings of conversations between a representative and one or more customers to generate multiple voice segments having a human voice, identifies the voice segments that have the same or a similar feature, and determines the voice in the identified voice segments as the voice of the representative.
Abstract:
The disclosure is directed to modeling calls in real time, with the goal of helping users, e.g., a sales representative and/or their managers, improve and/or guide the outcome of the calls. The embodiments generate real-time probabilities for possible outcomes of the conversation, as well as highlight specific on-call patterns, which may be either conducive or detrimental to a desired conversation outcome. The generated probabilities and highlighted patterns may be used by the sales representatives and/or their managers to either increase the probability of a desired outcome and/or optimize for call duration with a specific outcome.
Abstract:
A speaker identification system (“system”) automatically assigns a speaker to voiced segments in a conversation, without requiring any previously recorded voice sample or any other action by the speaker. The system enables unsupervised learning of speakers' fingerprints and using such fingerprints for identifying a speaker in a recording of a conversation. The system identifies one or more speakers, e.g., representatives of an organization, who are in conversation with other speakers, e.g., customers of the organization. The system processes recordings of conversations between a representative and one or more customers to generate multiple voice segments having a human voice, identifies the voice segments that have the same or a similar feature, and determines the voice in the identified voice segments as the voice of the representative.
Abstract:
The disclosure is directed to automatically determining deals at risk by analyzing conversations of representatives with customers. A risk identification system retrieves recordings of various conversations, extracts features of each of the conversations, and analyzes the features to determine if any of the conversations includes features that are indicative of a deal discussed in that conversation being at risk. By performing such an analysis of conversations, the risk identification system can identify a number of deals that are at risk and generate a report of such deals and notify a consumer user of the risk identification system of such deals.
Abstract:
A conference management system (“system”) facilitates data compliance in recording conversations between users. A host user can send an electronic invitation for a meeting to participants. Upon accessing the invitation, the participants can be presented with two options to join the conference—a first option using which a participant can join the meeting by providing consent to recording the meeting and a second option using which the participant can join the meeting by opting-out of recording of the meeting. When a participant opts-out of the recording of the meeting, the conference management system ensures that the recording is performed in compliance with a data compliance policy applicable to the participant who opted out of recording.
Abstract:
A call assistant device is used to command a call management system to perform a specified task in association with a specified call. The call assistant device can be an Internet of Things (IoT) based device, which can include one or more buttons and connect to a communication network wirelessly. When a user activates the call assistant device, e.g., presses a button, the call assistant device sends a message to the call management system to perform a specified task. Upon receiving the message, the call management system executes the specified task in association with a specified call of the user. The task to be performed can be any task that can be performed in association with a call, e.g., generating a summary of the call, bookmarking a specified moment in the call, sending a panic alert to a particular user, or generating an action item.
Abstract:
A feedback identification system to automatically determine customer pain points by analyzing conversations of representatives with customers. The feedback identification system retrieves recordings of various conversations, extracts features of the conversations, and analyzes the features to determine a set of features that is indicative of a customer pain point. A customer pain point is a problem the customer is facing with a product. The set of features is analyzed to generate a feedback manifest, which includes the customer pain point (a) as a summary of what is discussed in the conversations or (b) verbatim from the conversations.
Abstract:
A product functionality identification system to automatically determine product features that are a favorite of customers by analyzing conversations of representatives with the customers. The product functionality identification system retrieves recordings of various conversations, extracts features of the conversations, and analyzes the features to determine a set of features that is indicative of favorite functionalities of a product for one or more customers. A favorite functionality is one of multiple product features that is determined to be a favorite of one or more customers. The set of features is further analyzed to generate a favorite functionality manifest, which includes information regarding the favorite functionalities (a) as a summary of what is discussed in the conversations or (b) verbatim from the conversations.
Abstract:
A call assistant device is used to command a call management system to perform a specified task in association with a specified call. The call assistant device can be an Internet of Things (IoT) based device, which can include one or more buttons and connect to a communication network wirelessly. When a user activates the call assistant device, e.g., presses a button, the call assistant device sends a message to the call management system to perform a specified task. Upon receiving the message, the call management system executes the specified task in association with a specified call of the user. The task to be performed can be any task that can be performed in association with a call, e.g., generating a summary of the call, bookmarking a specified moment in the call, sending a panic alert to a particular user, or generating an action item.
Abstract:
A call-modeling system models calls in real-time, with the goal of helping users, e.g., a sales representative and/or their managers, improve and/or guide the outcome of the calls. The call-modeling system generates real-time probabilities for possible outcomes of the conversation, as well as highlight specific on-call patterns, which may be either conducive or detrimental to a desired conversation outcome. The generated probabilities and highlighted patterns may be used by the sales representatives and/or their managers to either increase the probability of a desired outcome and/or optimize for call duration with a specific outcome.