Patent classifications
H04M2203/40
LIVE AGENT RECOMMENDATION FOR A HUMAN-ROBOT SYMBIOSIS CONVERSATION SYSTEM
A computer-implemented method is presented for selecting a preferred live agent from a plurality of live agents. The method includes constructing, via the processor, a human expertise matrix pertaining to each of the plurality of live agents by determining an average net promoter score (NPS) for each of the plurality of live agents for each category of a plurality of categories, and in response to a voice call by a user, determining, via the processor, a predicted human expertise on average by collectively assessing the human expertise matrix, a predicted NPS derived from a first deep neural network, and a predicted category derived from a second deep neural network. The method further includes, based on the predicted human expertise on average determined, triggering communication via the live agent communication network between the user and the preferred live agent to initiate a conversation between the user and the preferred live agent.
VOICE AND SPEECH RECOGNITION FOR CALL CENTER FEEDBACK AND QUALITY ASSURANCE
A computer-implemented method for providing an objective evaluation to a customer service representative regarding his performance during an interaction with a customer may include receiving a digitized data stream corresponding to a spoken conversation between a customer and a representative; converting the data stream to a text stream; generating a representative transcript that includes the words from the text stream that are spoken by the representative; comparing the representative transcript with a plurality of positive words and a plurality of negative words; and generating a score that varies according to the occurrence of each word spoken by the representative that matches one of the positive words, and/or the occurrence of each word spoken by the representative that matches one of the negative words. Tone of voice, as well as response time, during the interaction may also be monitored and analyzed to adjust the score, or generate a separate score.
SYSTEM AND METHOD FOR CONTACT CENTER FAULT DIAGNOSTICS
A system and methods for contact center fault diagnostics, comprising a diagnostic engine and test cases used for testing components and services in a contact center, designed to operate on a contact center with a specified test campaign, allowing a contact center's various services and systems to be tested either internally or externally in an automated fashion with specified testcases being used to specify the format and expectations of a specific test, with reports of failures and points of failure being made available to system administrators.
Storing call session information in a telephony system
In an example of this disclosure, a method may include storing, by a first database server, first call session information in a data structure in a memory of the first database server. The first call session information may correspond to a unique identifier that corresponds to a caller. The method may include replicating the first call session information stored in the data structure in the memory of the first database server to a data structure in a memory of a second database server.
SPEAKER RECOGNITION IN THE CALL CENTER
Utterances of at least two speakers in a speech signal may be distinguished and the associated speaker identified by use of diarization together with automatic speech recognition of identifying words and phrases commonly in the speech signal. The diarization process clusters turns of the conversation while recognized special form phrases and entity names identify the speakers. A trained probabilistic model deduces which entity name(s) correspond to the clusters.
Voice and speech recognition for call center feedback and quality assurance
A computer-implemented method for providing an objective evaluation to a customer service representative regarding his performance during an interaction with a customer may include receiving a digitized data stream corresponding to a spoken conversation between a customer and a representative; converting the data stream to a text stream; generating a representative transcript that includes the words from the text stream that are spoken by the representative; comparing the representative transcript with a plurality of positive words and a plurality of negative words; and generating a score that varies according to the occurrence of each word spoken by the representative that matches one of the positive words, and/or the occurrence of each word spoken by the representative that matches one of the negative words. Tone of voice, as well as response time, during the interaction may also be monitored and analyzed to adjust the score, or generate a separate score.
Speaker recognition in the call center
Utterances of at least two speakers in a speech signal may be distinguished and the associated speaker identified by use of diarization together with automatic speech recognition of identifying words and phrases commonly in the speech signal. The diarization process clusters turns of the conversation while recognized special form phrases and entity names identify the speakers. A trained probabilistic model deduces which entity name(s) correspond to the clusters.
SPEAKER RECOGNITION IN THE CALL CENTER
Utterances of at least two speakers in a speech signal may be distinguished and the associated speaker identified by use of diarization together with automatic speech recognition of identifying words and phrases commonly in the speech signal. The diarization process clusters turns of the conversation while recognized special form phrases and entity names identify the speakers. A trained probabilistic model deduces which entity name(s) correspond to the clusters.
System and method for contact center fault diagnostics
A system and methods for contact center fault diagnostics, comprising a diagnostic engine and test cases used for testing components and services in a contact center, designed to operate on a contact center with a specified test campaign, allowing a contact center's various services and systems to be tested either internally or externally in an automated fashion with specified testcases being used to specify the format and expectations of a specific test, with reports of failures and points of failure being made available to system administrators.
Dialing list manager for outbound calls
A dialing list is managed, with human intervention, by obtaining a proposed call list for to-be-called (TBC) parties from a source, which list is displayed to a call center (CC) agent who selects one or more TBC parties, which causes generation of an agent-approved (AA) call list. Outbound calls are made using the AA call list. TBC parties not selected are not called by the dialing platform. The dialing platform responsive in-bound calls and non-productive (NP) calls. The AA call list is supplemented with NP call data such that TBC parties are linked to NP call data, thereby creating a productive TBC call list. A telecom session is initiated between the CC agent and the TBC called party.