Abstract: A computer system may communicate metadata that identifies a current speaker. The computer system may receive audio data that represents speech of the current speaker, generate an audio fingerprint of the current speaker based on the audio data, and perform automated speaker recognition by comparing the audio fingerprint of the current speaker against stored audio fingerprints contained in a speaker fingerprint repository. The computer system may communicate data indicating that the current speaker is unrecognized to a client device of an observer and receive tagging information that identifies the current speaker from the client device of the observer. The computer system may store the audio fingerprint of the current speaker and metadata that identifies the current speaker in the speaker fingerprint repository and communicate the metadata that identifies the current speaker to at least one of the client device of the observer or a client device of a different observer.

Abstract: A computer system automatically generates service documentation based on usage of a web service. The computer system captures network traffic including actual requests to a service endpoint of the web service and actual responses from the service endpoint of the web service. The captured network traffic can be analyzed using machine learning to determine one or more operations that are available at the service endpoint, input arguments that are accepted by the service endpoint, and output arguments that are provided by the service endpoint. The computer system can automatically generate service documentation for the web service based on metadata that identifies the operations, the input arguments, and the output arguments.

Abstract: User-specific data for use with a software service may be stored in an encrypted form, where the encryption and/or decryption keys used are associated with a user's biometric data (that the user voluntarily provides after appropriate disclosure, to protect the user's interest in privacy). When the user uses the software service on a device, the device may receive the user-specific data in an encrypted form, and then may use the biometric data to retrieve or generate the cryptographic key that is used to decrypt the user-specific data. The user-specific data is then decrypted and used on the device with the software service.

Abstract: A computer system may communicate metadata that identifies a current speaker. The computer system may receive audio data that represents speech of the current speaker, generate an audio fingerprint of the current speaker based on the audio data, and perform automated speaker recognition by comparing the audio fingerprint of the current speaker against stored audio fingerprints contained in a speaker fingerprint repository. The computer system may communicate data indicating that the current speaker is unrecognized to a client device of an observer and receive tagging information that identifies the current speaker from the client device of the observer. The computer system may store the audio fingerprint of the current speaker and metadata that identifies the current speaker in the speaker fingerprint repository and communicate the metadata that identifies the current speaker to at least one of the client device of the observer or a client device of a different observer.

Abstract: A computer system may communicate metadata that identifies a current speaker. The computer system may receive audio data that represents speech of the current speaker, generate an audio fingerprint of the current speaker based on the audio data, and perform automated speaker recognition by comparing the audio fingerprint of the current speaker against stored audio fingerprints contained in a speaker fingerprint repository. The computer system may communicate data indicating that the current speaker is unrecognized to a client device of an observer and receive tagging information that identifies the current speaker from the client device of the observer. The computer system may store the audio fingerprint of the current speaker and metadata that identifies the current speaker in the speaker fingerprint repository and communicate the metadata that identifies the current speaker to at least one of the client device of the observer or a client device of a different observer.

Abstract: A device set may interoperate to perform an action, such as providing a message to a user or storing photos taken by a user. Performing the action on all available devices may cause redundancy (e.g., presenting the same message to the user on each device), and depending on user selection (e.g., the user requesting to play music and specifically designating a device) may become onerous. A centralized, server-driven selection of the device to perform the action may be problematic if the server is inaccessible and/or inaccurate if not currently informed of the current state of each device. In accordance with the techniques presented herein, a requesting device broadcasts an action invitation to the device set. Each device provides a suitability report indicating its suitability to perform the action. The requesting device identifies one or more suitable devices, and sends an action request to identified devices to perform the action.

Abstract: A computer system automatically generates service documentation based on usage of a web service. The computer system captures network traffic including actual requests to a service endpoint of the web service and actual responses from the service endpoint of the web service. The captured network traffic can be analyzed using machine learning to determine one or more operations that are available at the service endpoint, input arguments that are accepted by the service endpoint, and output arguments that are provided by the service endpoint. The computer system can automatically generate service documentation for the web service based on metadata that identifies the operations, the input arguments, and the output arguments.

Abstract: A computer system may communicate metadata that identifies a current speaker. The computer system may receive audio data that represents speech of the current speaker, generate an audio fingerprint of the current speaker based on the audio data, and perform automated speaker recognition by comparing the audio fingerprint of the current speaker against stored audio fingerprints contained in a speaker fingerprint repository. The computer system may communicate data indicating that the current speaker is unrecognized to a client device of an observer and receive tagging information that identifies the current speaker from the client device of the observer. The computer system may store the audio fingerprint of the current speaker and metadata that identifies the current speaker in the speaker fingerprint repository and communicate the metadata that identifies the current speaker to at least one of the client device of the observer or a client device of a different observer.

Abstract: Many devices are configured to present alerts notifying a user of device events, but the user may not notice the alert due to a noisy environment. A user may mitigate missed alerts by increasing the alert volume or choosing a vibration mode, but such techniques depend upon the knowledge, attention, and memory of the user to adjust the device before the alert. Instead, a device may compare the noise level of the environment with a noise level threshold. If the noise level is below the threshold, the device presents the alert; but if the noise level is above the threshold, the device defers the presentation of the alert until the noise level diminishes below the threshold, and then presents the alert. The device may also send an automated response to the message, notifying a sender that the user may return the message upon leaving the noisy environment.

Abstract: User-specific data for use with a software service may be stored in an encrypted form, where the encryption and/or decryption keys used are associated with a user's biometric data (that the user voluntarily provides after appropriate disclosure, to protect the user's interest in privacy). When the user uses the software service on a device, the device may receive the user-specific data in an encrypted form, and then may use the biometric data to retrieve or generate the cryptographic key that is used to decrypt the user-specific data. The user-specific data is then decrypted and used on the device with the software service.

Abstract: In many scenarios, a device may detect one or more audio conversations, and may be capable of evaluating such audio conversations, e.g., in order to present a text transcript to a user. However, the user's attention to such audio conversations may waver, and the user may miss the audio conversation and/or an opportunity to participate in the audio conversation. Presented herein are techniques for enabling devices to assist users in such scenarios by monitoring audio conversations to detect conversation cues that pertain to the user (e.g., the user's name, names of the user's friends, and/or topics of interest to the user). Upon detecting a conversation cue within an audio conversation that pertains to the user, the device notifies the user (e.g., alerting the user that the audio conversation may be of interest, and/or presenting a text transcript of the portion of the audio conversation containing the conversation cue).

Abstract: A device set may interoperate to perform an action, such as providing a message to a user or storing photos taken by a user. Performing the action on all available devices may cause redundancy (e.g., presenting the same message to the user on each device), and depending on user selection (e.g., the user requesting to play music and specifically designating a device) may become onerous. A centralized, server-driven selection of the device to perform the action may be problematic if the server is inaccessible and/or inaccurate if not currently informed of the current state of each device. In accordance with the techniques presented herein, a requesting device broadcasts an action invitation to the device set. Each device provides a suitability report indicating its suitability to perform the action. The requesting device identifies one or more suitable devices, and sends an action request to identified devices to perform the action.

Abstract: Many devices are configured to present alerts notifying a user of device events, but the user may not notice the alert due to a noisy environment. A user may mitigate missed alerts by increasing the alert volume or choosing a vibration mode, but such techniques depend upon the knowledge, attention, and memory of the user to adjust the device before the alert. Instead, a device may compare the noise level of the environment with a noise level threshold. If the noise level is below the threshold, the device presents the alert; but if the noise level is above the threshold, the device defers the presentation of the alert until the noise level diminishes below the threshold, and then presents the alert. The device may also send an automated response to the message, notifying a sender that the user may return the message upon leaving the noisy environment.