Implementations relate to techniques for providing context-dependent search results. A computer-implemented method includes receiving an audio stream at a computing device during a time interval, the audio stream comprising user speech data and background audio, separating the audio stream into a first substream that includes the user speech data and a second substream that includes the background audio, identifying concepts related to the background audio, generating a set of terms related to the identified concepts, influencing a speech recognizer based on at least one of the terms related to the background audio, and obtaining a recognized version of the user speech data using the speech recognizer.

Implementations relate to techniques for providing context-dependent search results. A computer-implemented method includes receiving an audio stream at a computing device during a time interval, the audio stream comprising user speech data and background audio, separating the audio stream into a first substream that includes the user speech data and a second substream that includes the background audio, identifying concepts related to the background audio, generating a set of terms related to the identified concepts, influencing a speech recognizer based on at least one of the terms related to the background audio, and obtaining a recognized version of the user speech data using the speech recognizer.

Processing stacked data structures is provided. A system receives an input audio signal detected by a sensor of a local computing device, identifies an acoustic signature, and identifies an account corresponding to the signature. The system establishes a session and a profile stack data structure including a first profile layer having policies configured by a third-party device. The system pushes, to the profile stack data structure, a second profile layer retrieved from the account. The system parses the input audio signal to identify a request and a trigger keyword. The system generates, based on the trigger keyword and the second profile layer, a first action data structure compatible with the first profile layer. The system provides the first action data structure for execution. The system disassembles the profile stack data structure to remove the first profile layer or the second profile layer from the profile stack data structure.

Processing stacked data structures is provided. A system receives an input audio signal detected by a sensor of a local computing device, identifies an acoustic signature, and identifies an account corresponding to the signature. The system establishes a session and a profile stack data structure including a first profile layer having policies configured by a third-party device. The system pushes, to the profile stack data structure, a second profile layer retrieved from the account. The system parses the input audio signal to identify a request and a trigger keyword. The system generates, based on the trigger keyword and the second profile layer, a first action data structure compatible with the first profile layer. The system provides the first action data structure for execution. The system disassembles the profile stack data structure to remove the first profile layer or the second profile layer from the profile stack data structure.

An embodiment of a spoken intent detection device includes technology to detect a phrase in an electronic representation of an audio stream based on a pre-defined vocabulary, associate a time stamp with the detected phrase, and classify a spoken intent based on a sequence of detected phrases and the respective associated time stamps. Other embodiments are disclosed and claimed.

Controlled-environment facility resident behavioral and/or health monitoring may employ controlled-environment facility resident wearables each having a band configured to be affixed around a portion of a controlled-environment facility resident, irremovable by the resident and may include sensor(s) configured to measure biometric(s) of the controlled-environment facility resident and one or more physical parameter(s) experienced by the wearable, with a transmitter transmitting the biometric(s) and/or the physical parameter(s) to a controlled-environment facility management system. The controlled-environment facility management system may predetermine one or more normal input levels of the biometric(s) and/or physical parameter(s), receive the transmitted biometric(s) and/or physical parameter(s), determine whether received biometric(s) and/or physical parameter(s) rises above or falls below the predetermined normal input level(s), and alert controlled-environment facility personnel and/or law enforcement when received physical parameter(s) and/or received biometric(s) rise above or fall below the predetermined normal input level(s).

Controlled-environment facility resident behavioral and/or health monitoring may employ controlled-environment facility resident wearables each having a band configured to be affixed around a portion of a controlled-environment facility resident, irremovable by the resident and may include sensor(s) configured to measure biometric(s) of the controlled-environment facility resident and one or more physical parameter(s) experienced by the wearable, with a transmitter transmitting the biometric(s) and/or the physical parameter(s) to a controlled-environment facility management system. The controlled-environment facility management system may predetermine one or more normal input levels of the biometric(s) and/or physical parameter(s), receive the transmitted biometric(s) and/or physical parameter(s), determine whether received biometric(s) and/or physical parameter(s) rises above or falls below the predetermined normal input level(s), and alert controlled-environment facility personnel and/or law enforcement when received physical parameter(s) and/or received biometric(s) rise above or fall below the predetermined normal input level(s).

Prevention of voice misappropriation in voice interaction/response systems. The system relies on telemetry data, including thermal data of components to determine whether a received voice command was made by actual voice. If the voice command is determined to have been made by an actual voice, a response to the command is generated and transmitted, otherwise if the voice command is determined to have likely not been made by an actual voice (e.g., artificial means replicating a voice, such as a laser or the like), no response to the command is transmitted or action taken with respect to the command.

Prevention of voice misappropriation in voice interaction/response systems. The system relies on telemetry data, including thermal data of components to determine whether a received voice command was made by actual voice. If the voice command is determined to have been made by an actual voice, a response to the command is generated and transmitted, otherwise if the voice command is determined to have likely not been made by an actual voice (e.g., artificial means replicating a voice, such as a laser or the like), no response to the command is transmitted or action taken with respect to the command.

A method and system for implementing a speech-enabled interface of a host device via an electronic mobile device in a network are provided. The method includes establishing a communication session between the host device and the mobile device via a session service provider. According to some embodiments, a barcode can be adopted to enable the pairing of the host device and mobile device. Furthermore, the present method and system employ the voice interface in conjunction with speech recognition systems and natural language processing to interpret voice input for the hosting device, which can be used to perform one or more actions related to the hosting device.