A system enhances existing audio-visual content with audio describing the setting of the visual content. A scene annotation module classifies scene elements from an image frame received from a host system and generates a caption describing the scene elements. A text to speech synthesis module may then convert the caption to synthesized speech data describing the scene elements within the image frame

A system enhances existing audio-visual content with audio describing the setting of the visual content. A scene annotation module classifies scene elements from an image frame received from a host system and generates a caption describing the scene elements. A text to speech synthesis module may then convert the caption to synthesized speech data describing the scene elements within the image frame

The techniques herein are directed generally to methods and apparatus for automatically classifying interactions with contact center, identifying contacts as being initiated by one of a normal user, a malicious actor, an inexperienced user, or a new type of a user, and invoking mitigation actions such as forwarding the caller to a dedicated agent group based on the identification.

The techniques herein are directed generally to methods and apparatus for automatically classifying interactions with contact center, identifying contacts as being initiated by one of a normal user, a malicious actor, an inexperienced user, or a new type of a user, and invoking mitigation actions such as forwarding the caller to a dedicated agent group based on the identification.

Methods and systems for capturing and processing audio data of a vehicle engine. In one aspect, a vehicle audio capture system includes a mobile device configured to capture vehicle engine sounds in an audio file and to associate tags identifying one or more vehicle conditions observed during audio capture and reflected in the audio file, and a server configured to process the audio file and expose an application programming interface (API) to provide access to the audio file to one or more data consumer devices. In some instances, a condition report server is configured to access the application programming interface to retrieve a version of the audio file and include data describing the audio file within a vehicle condition report. Additionally, tags may be added to the audio file based on detected engine conditions. Detection of engine conditions may be based on use of trained models.

Methods and systems for capturing and processing audio data of a vehicle engine. In one aspect, a vehicle audio capture system includes a mobile device configured to capture vehicle engine sounds in an audio file and to associate tags identifying one or more vehicle conditions observed during audio capture and reflected in the audio file, and a server configured to process the audio file and expose an application programming interface (API) to provide access to the audio file to one or more data consumer devices. In some instances, a condition report server is configured to access the application programming interface to retrieve a version of the audio file and include data describing the audio file within a vehicle condition report. Additionally, tags may be added to the audio file based on detected engine conditions. Detection of engine conditions may be based on use of trained models.

A method, computer program product, and computing system for receiving information associated with an acoustic environment. Acoustic metadata associated with audio encounter information received by a first microphone system may be received. One or more speaker representations may be defined based upon, at least in part, the acoustic metadata associated with the audio encounter information and the information associated with the acoustic environment. One or more portions of the audio encounter information may be labeled with the one or more speaker representations and a speaker location within the acoustic environment.

A method, computer program product, and computing system for receiving information associated with an acoustic environment. Acoustic metadata associated with audio encounter information received by a first microphone system may be received. One or more speaker representations may be defined based upon, at least in part, the acoustic metadata associated with the audio encounter information and the information associated with the acoustic environment. One or more portions of the audio encounter information may be labeled with the one or more speaker representations and a speaker location within the acoustic environment.

Custom alerts may be generated based on sound type indicators determined using a machine learning classification model trained on user-provided sound recordings and user-defined sound type indicators. A device may provide a sound recording and a type indicator identifying an entity that made a sound in the recording for storage in a database that includes a plurality sound recordings associated with a plurality of type indicators. A machine learning classification model may be trained based on the stored recordings, including the user-defined recordings. The model may be used to classify sounds recorded by other devices and generate alerts identifying the type of sound. Thus, multiple users may contribute data to customize machine learning models that recognize sounds and generate alerts based on user-defined identifiers.

A system, computer program product, and method are provided for use with an intelligent computer platform to identify intent and convert the intent to one or more physical actions. The aspect of converting intent includes receiving content, identifying potential variants, and statistically analyzing the variants with a confidence assessment. The variants are sorted based on a protocol associated with the confidence assessment. A variant from the sort is selected and applied to a physical device, which performs a physical action and an associated hardware transformation based on the variant.