Abstract: Examples for augmenting user recognition via speech are provided. One example method comprises, on a computing device, monitoring a use environment via one or more sensors including an acoustic sensor, detecting utterance of a key phrase via data from the acoustic sensor, and based upon the selected data from the acoustic sensor and also on other environmental sensor data collected at different times than the selected data from the acoustic sensor, determining a probability that the key phrase was spoken by an identified user. The method further includes, if the probability meets or exceeds a threshold probability, then performing an action on the computing device.

Abstract: Examples for augmenting user recognition via speech are provided. One example method comprises, on a computing device, monitoring a use environment via one or more sensors including an acoustic sensor, detecting utterance of a key phrase via data from the acoustic sensor, and based upon the selected data from the acoustic sensor and also on other environmental sensor data collected at different times than the selected data from the acoustic sensor, determining a probability that the key phrase was spoken by an identified user. The method further includes, if the probability meets or exceeds a threshold probability, then performing an action on the computing device.

Abstract: Examples for augmenting user recognition via speech are provided. One example method comprises, on a computing device, monitoring a use environment via one or more sensors including an acoustic sensor, detecting utterance of a key phrase via data from the acoustic sensor, and based upon the selected data from the acoustic sensor and also on other environmental sensor data collected at different times than the selected data from the acoustic sensor, determining a probability that the key phrase was spoken by an identified user. The method further includes, if the probability meets or exceeds a threshold probability, then performing an action on the computing device.

Abstract: Computing devices and methods for providing speech recognition data from one computing device to another device are disclosed. In one disclosed embodiment, audio input is received at a client device and processed to generate speech recognition data. An estimated confidence level is determined for a portion of the data, where the confidence level exceeds a predetermined confidence threshold corresponding to a valid result. At least one statistically improbable characteristic associated with the portion of data is identified. Based on identifying the statistically improbable characteristic, the portion of data is provided to a server computing device for evaluation.

Abstract: Techniques for integrating a virtual assistant into a spoken conversation session, the techniques including receiving an utterance information that expresses an utterance spoken by a first participant included in a plurality of participants of a spoken conversation session; processing the utterance information using at least one machine-trained model to determine an intent or content for a command or query included in the utterance; selectively identifying a recipient subset of one or more of the plurality of participants based on at least the determined intent or content for the utterance; generating a response for the command or query; and providing, during the spoken conversation session, the response to the identified recipient subset.

Abstract: Techniques for integrating a virtual assistant into a spoken conversation session, the techniques including receiving an utterance information that expresses an utterance spoken by a first participant included in a plurality of participants of a spoken conversation session; processing the utterance information using at least one machine-trained model to determine an intent or content for a command or query included in the utterance; selectively identifying a recipient subset of one or more of the plurality of participants based on at least the determined intent or content for the utterance; generating a response for the command or query; and providing, during the spoken conversation session, the response to the identified recipient subset.

Abstract: An improved method and system for enhancing a user's experience within an immersive environment is disclosed. Solutions and implementations provided improve the user's ability to both hear and identify sounds from outside the user's immersive experience. Implementations include receiving audio and sensor input from the environment, analyzing the received input and adjusting either the display or audio outputs generated for the user based in part on pre-determined policies.

Abstract: An improved method and system for enhancing a user's experience within an immersive environment is disclosed. Solutions and implementations provided improve the user's ability to both hear and identify sounds from outside the user's immersive experience. Implementations include receiving audio and sensor input from the environment, analyzing the received input and adjusting either the display or audio outputs generated for the user based in part on pre-determined policies.

Abstract: Various embodiments relating to adjusting a variable audio parameter of a game are provided. In one embodiment, based on a user ability level, a variable audio parameter of the game is adjusted to an adjusted audio parameter that either increases the difficulty level of the game or decrease the difficulty level of the game. The adjusted audio parameter is utilized to provide audio content of the game to a user via an electronic gaming machine.

Abstract: Optimizations are provided for improving the collection and transmission of sensor collected data. In particular, sensor related data is initially collected. Then, a determination is made regarding a state of an anticipated recipient of the collected sensor related data. Based on the state of the anticipated recipient, a determination is made regarding a representation of the sensor collected data. At least some of this sensor collected data is then delivered to the anticipated recipient in the determined representation.

Abstract: Computing devices and methods for providing speech recognition data from one computing device to another device are disclosed. In one disclosed embodiment, audio input is received at a client device and processed to generate speech recognition data. An estimated confidence level is determined for a portion of the data, where the confidence level exceeds a predetermined confidence threshold corresponding to a valid result. At least one statistically improbable characteristic associated with the portion of data is identified. Based on identifying the statistically improbable characteristic, the portion of data is provided to a server computing device for evaluation.

Abstract: Optimizations are provided for improving the collection and transmission of sensor collected data. In particular, sensor related data is initially collected. Then, a determination is made regarding a state of an anticipated recipient of the collected sensor related data. Based on the state of the anticipated recipient, a determination is made regarding a representation of the sensor collected data. At least some of this sensor collected data is then delivered to the anticipated recipient in the determined representation.

Abstract: Various technologies described herein pertain to using detected physical gestures to cause calls to transfer between client devices. A physical gesture between a first client device and a second client device can be detected (e.g., utilizing the first client device, the second client device, a disparate client-side device, a server, etc.). The first client device participates in a call, while the second client device is not participating in the call at a time of the detection of the physical gesture. Responsive to detection of the physical gesture, participation of the second client device in the call can be initiated. Participation of the second client device in the call can be initiated by causing the call to transfer from the first client device to the second client device or causing the second client device to join the call while the first client device continues to participate in the call.

Abstract: A system estimates environment-specific alterations of a user sound received at the system. The system modifies the received user sound to formulate a modified user sound by at least compensating for the audio modifications and/or formulates an expected audio model of a user by modifying a stored user-dependent audio model of the user with the audio modification. The system is also capable of estimating whether the received user sounds is from a particular user by use of a corresponding user-dependent audio model.

Abstract: Providing sensor collected data. The data is related to sensor collected data. The method includes collecting sensor related data. The method further includes determining a state of an anticipated recipient of the collected sensor related data. The method further includes, based on the state of the anticipated recipient, determining a representation of the sensor collected data. The method further includes sending the sensor collected data in the determined representation.

Abstract: A system estimates environment-specific alterations of a user sound received at the system. The system modifies the received user sound to formulate a modified user sound by at least compensating for the audio modifications and/or formulates an expected audio model of a user by modifying a stored user-dependent audio model of the user with the audio modification. The system is also capable of estimating whether the received user sounds is from a particular user by use of a corresponding user-dependent audio model.

Abstract: Various technologies described herein pertain to using detected physical gestures to cause calls to transfer between client devices. A physical gesture between a first client device and a second client device can be detected (e.g., utilizing the first client device, the second client device, a disparate client-side device, a server, etc.). The first client device participates in a call, while the second client device is not participating in the call at a time of the detection of the physical gesture. Responsive to detection of the physical gesture, participation of the second client device in the call can be initiated. Participation of the second client device in the call can be initiated by causing the call to transfer from the first client device to the second client device or causing the second client device to join the call while the first client device continues to participate in the call.

Abstract: Computerized estimation of an identity of a user of a computing system. The system estimates environment-specific alterations of a received user sound that is received at the computing system. The system estimates whether the received user sounds is from a particular user by use of a corresponding user-dependent audio model. The user-dependent audio model may be stored in a multi-system store accessible such that the method may be performed for a given user across multiple systems and on a system that the user has never before trained to recognize the user. This reduces or even eliminates the need for a user to train a system to recognize the voice of a user, and allows multiple systems to take advantage of previous training performed by the user.

Abstract: Various embodiments relating to adjusting a variable audio parameter of a game are provided. In one embodiment, based on a user ability level, a variable audio parameter of the game is adjusted to an adjusted audio parameter that either increases the difficulty level of the game or decrease the difficulty level of the game. The adjusted audio parameter is utilized to provide audio content of the game to a user via an electronic gaming machine.

Abstract: Computerized estimation of an identity of a user of a computing system. The system estimates environment-specific alterations of a received user sound that is received at the computing system. The system estimates whether the received user sounds is from a particular user by use of a corresponding user-dependent audio model. The user-dependent audio model may be stored in a multi-system store accessible such that the method may be performed for a given user across multiple systems and on a system that the user has never before trained to recognize the user. This reduces or even eliminates the need for a user to train a system to recognize the voice of a user, and allows multiple systems to take advantage of previous training performed by the user.