Avaya Inc.

Wendy J Holmes

Keith M Ponting

David Skiba

Mehmet Balasaygun

John F Buford

John Jacob

Embodiments disclosed herein provide systems, methods, and computer-readable media for detecting disturbances in a media stream from a participant on a communication. In a particular embodiment, a method provides receiving biometric information indicating a motion of the participant and determining that the motion indicates a visual disturbance in a video component of the first media stream. The method further provides identifying the visual disturbance in the video component of the first media stream and removing the visual disturbance from the video component of the first media stream.

Disturbance detection in video communications

A method, system, and phonetic search engine are described that enable phonetic searches to have increased relevancy to the searcher. Specifically, phonetic searches on a database containing phonetically-searchable content can have one or more phonetically-confusable terms included therein, thereby creating search results that more faithfully reflect the search terms used during the phonetic search of the database.

Organizing speech search results

Embodiments disclosed herein provide systems, methods, and computer readable media for detecting disturbances in a media stream from a participant on a communication. In a particular embodiment, a method provides identifying disturbance criteria defining a plurality of audible disturbances, a plurality of visual disturbances, and a plurality of communication disturbances. The method further provides identifying one or more audible disturbances from an audio component of the media stream based on predefined disturbance criteria and identifying one or more visual disturbances from a video component of the media stream based on the disturbance criteria. Additionally, the method provides correlating the audible disturbances with the visual disturbances to determine one or more combined disturbances for the participant based on the disturbance criteria, wherein each of the combined disturbances comprises at least one of the audible disturbances and at least one of the visual disturbances.

An event associated with a communication session between a first party and a second party is detected. The event is related to the communication session. For example, the event may be a phrase spoken in the communication session or a presentation of a call progression screen to a contact center agent. At this point, the communication session is analyzed for a period of non-communication that meets a defined threshold during a monitoring period associated with the event. If a period of non-communication is detected that is longer than the threshold during the monitoring period, the period of non-communication is flagged. The flagged period of non-communication can then be used to evaluate how a contact center agent is performing.

Silence density models

To detect events in an audio stream, frames of an audio signal (e.g., frames generated by a codec for a voice call or music stream) are received. Based on information in the frames, an index is used to look up an entry in a table associated with the codec. Each entry in the table indicates a likelihood that a frame matches a sound model element. The likelihood is used in the search for a sound bite, word, and/or phrase in the audio signal. The process of dynamic programming is used to find the combined likelihood for a match of the word, phrase, and/or sound bite to a region of the audio stream. Upon detection of the word, phrase, and/or sound bite in the audio stream, an event is generated, such as, notifying a person or logging the event in a database.

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Worcestershire, United Kingdom

Wendy J Holmes