Affectlayer, Inc.

Zoominfo Converse LLC

Russell Levy

Micha Yochanan Breakstone

Roy Raanani

Dominik Facher

Erez Volk

Raphael Cohen

Orgad Keller

Ilana Tuil

Amit Ashkenazi

A conference management 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.

Data compliance management in recording calls

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&#x2014;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.

A speaker identification system ('system') automatically assigns a speaker to voiced segments in a call. The system identifies one or more speakers in a call using one or more speaker-identification parameters. The system processes the call to determine one or more speaker-identification parameters, such as a transcript of the call, a facial image of the speaker, a scene image, which is an image of a scene in which the speaker is located during the call, or textual data associated with the call such as names of the speaker or an organization that are retrieved from the scene images or video data of the call. The system analyzes one or more of the speaker-identification parameters and determines the identity of the speaker. The system then identifies the voice segments associated with the identified speaker and marks the voice segments with the identity of the speaker.

Automatic speaker identification in calls using multiple speaker-identification parameters

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.

IoT-based call assistant device

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.

Modeling voice calls to improve an outcome of a call between a representative and a customer

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.

Automatic speaker identification in calls

An in-call virtual assistant system monitors a real-time call, e.g., a call that is in progress, between multiple speakers, identifies a trigger and executes a specified task in response to the trigger. The virtual assistant system can be invoked by an explicit trigger or an implicit trigger. For example, an explicit trigger can be a voice command from one of the speakers in the call, such as 'Ok Chorus, summarize the call' for summarizing the call. An implicit trigger can be an event that occurred in the call, or outside of the call but that is relevant to a speaker. For example, an event such as a speaker dropping off the call suddenly can be an implicit trigger that invokes the virtual assistant system to perform an associated task, such as notifying the remaining speakers on the call that one of the speakers dropped.

In-call virtual assistant

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.

Analyzing conversations to automatically identify customer pain points

A feedback identification system to automatically determine product feature requests 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 feature request. A feature request is a request for adding a specified functionality to a product. The set of features is analyzed to generate a feedback manifest, which includes the feature request (a) as a summary of what is discussed in the conversations or (b) verbatim from the conversations.

Analyzing conversations to automatically identify product feature requests

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.

Analyzing conversations to automatically identify product features that resonate with customers

A moment identification system automatically generates a playlist of conversations having a specified moment. A moment can be occurrence of a specific event or a specific characteristic in a conversation, or any event that is of specific interest for an application for which the playlist is being generated. For example, a moment can include laughter, fast-talking, objections, response to questions, a discussion on a particular topic such as budget, behavior of a speaker, intent to buy, etc., in a conversation. The moment identification system analyzes each of the conversations to determine if one or more features of a conversation correspond to a specified moment, and includes those of the conversations in the playlist having one or more features that correspond to the specified moment. The playlist may include a portion of a conversation that has the specified moment rather than the entire conversation.

Automatic generation of playlists from conversations

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

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Raanana, Israel

Russell Levy