H04M2203/40

SYSTEM AND METHOD FOR DETECTING FRAUD RINGS

A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

Contextual multi-channel speech to text

A method for improving a transcription may include identifying, in the transcription, reliable channel tokens of an utterance of a reliable channel and an unreliable channel token of an utterance of an unreliable channel, and generating, using a machine learning model, a vector embedding for the unreliable channel token and vector embeddings for the reliable channel tokens. The method may further include calculating vector distances between the vector embedding and the vector embeddings, and generating, for the unreliable channel token and using the vector distances, a score corresponding to a reliable channel token. The method may further include determining that the score is within a threshold score, and in response to determining that the score is within the threshold score, replacing, in the transcription, the unreliable channel token with the reliable channel token.

SPEAKER RECOGNITION IN THE CALL CENTER
20230326462 · 2023-10-12 · ·

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.

Gesture-based call center agent state change control

Users of a networked communication device may omit updating their availability state, and that of an associated communication device, if the state change is sudden or believed to be of sufficiently short duration. By quickly changing their state, a routing component may more accurately know whether or not a communication routed to the communication device will or will not be answered. By utilizing a camera and gesture processing logic, a user may naturally and quickly update their state without the need to navigate menus or select options with manual, tactile interactions with the communication device.

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.

Contact center network and method for establishing a communication session in a contact center network

A contact center network including a contact center unit connected via a communication network to a plurality of agents and to a plurality of IoT devices, wherein each one of the plurality of IoT devices is equipped with sensor devices adapted to measure predetermined IoT measurement data, and at least one actuator device adapted to control the IoT device remotely, wherein the contact center unit is connectable to the sensor devices and the actuator devices via a IoT middleware unit adapted to receive an incident notification, if sensor measurement data matches a predetermined criterion indicating an incident, and wherein the contact center unit includes a routing unit adapted to route a contact based on the incident information comprised in the incident notification to an agent. Further, embodiments relate to a method for establishing a communication session in a contact center network.

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.

GENERATING ACTION ITEMS DURING A CONFERENCING SESSION
20220301557 · 2022-09-22 ·

Embodiments include systems and methods for receiving an action item trigger by a user of a conferencing application; and in response to receiving the action item trigger, generating spoken words from audio data of a session of the conferencing application; normalizing the spoken words; generating higher-level representations of the normalized spoken words; determining semantic similarities of the higher-level representations of the normalized spoken words and higher level representations of normalized action words of an action word list; ranking options for top spoken words and action words based at least in part on the semantic similarities; identifying candidates for action words and/or phrases from the top spoken words and action words; and parsing the candidates to generate one or more action items.

GESTURE-BASED CALL CENTER AGENT STATE CHANGE CONTROL
20220094782 · 2022-03-24 ·

Users of a networked communication device may omit updating their availability state, and that of an associated communication device, if the state change is sudden or believed to be of sufficiently short duration. By quickly changing their state, a routing component may more accurately know whether or not a communication routed to the communication device will or will not be answered. By utilizing a camera and gesture processing logic, a user may naturally and quickly update their state without the need to navigate menus or select options with manual, tactile interactions with the communication device.

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.