Abstract: An adjustable back restaurant highchair is a restaurant style highchair with an adjustable back system. The back section of the highchair moves in its entirety, forward and backward along the seat section. Each corner of the seat back is provided with a pin that rides in four (4) corresponding adjustable tracks. Movement is enabled when a parent or care provider lifts the seat back up slightly, slides it forward or backward, and lowers it back into the tracks. Such adjustability accommodates children of all sizes, while ensuring that the smallest of them remain upright and cannot slide down. This eliminates the current practice of bracing the child up with towels, blankets, or coats, that are jammed in between their back and the seat support. The device remains stackable and keeps the simple design of its conventional counterpart.

Abstract: A server transmits an encoded game frame over a network to a respective client system as a set of packets. In response to transmitting the set of packets, the server determines a bandwidth estimate based on the size of the encoded game frame and the timing data associated with the transmitted set of packets. The server then compares the bandwidth estimate to a current video bitrate of the game stream being transmitted from the server to the respective client device. In response to the comparison indicating an underutilization of the network, the server increases the encoding bitrate. Further, in response to the comparison indication an overutilization of the network, the server decreases the encoding bitrate.

Abstract: As noted above, example techniques relate to offline voice control. A local voice input engine may process voice inputs locally when processing voice inputs via a cloud-based voice assistant service is not possible. Some techniques involve local (on-device) voice-assisted set-up of a cloud-based voice assistant service. Further example techniques involve local voice-assisted troubleshooting the cloud-based voice assistant service. Other techniques relate to interactions between local and cloud-based processing of voice inputs on a device that supports both local and cloud-based processing.

Abstract: As noted above, example techniques relate to toggling a cloud-based VAS between enabled and disabled modes. An example implementation involves a NMD detecting that the housing is in a first orientation and enabling a first mode. Enabling the first mode includes disabling voice input processing via a cloud-based VAS and enabling local voice input processing. In the first mode, the NMD captures sound data associated with a first voice input and detects, via a local natural language unit, that the first voice input comprises sound data matching one or more keywords. The NMD determines an intent of the first voice input and performs a first command according to the determined intent. The NMD may detect that the housing is in a second orientation and enables the second mode. Enabling the second mode includes enabling voice input processing via the cloud-based VAS.

Abstract: Provided herein are purification, production and manufacturing methods for recombinant viral vector particles such as recombinant adeno-associated viral (rAAV) vector particles substantially free of empty viral particles; a population of recombinant adeno-associated vims (rAAV) particles purified using the method described herein, and a pharmaceutical composition comprising the purified rAAV.

Abstract: As noted above, example techniques relate to offline voice control. A local voice input engine may process voice inputs locally when processing voice inputs via a cloud-based voice assistant service is not possible. Some techniques involve local (on-device) voice-assisted set-up of a cloud-based voice assistant service. Further example techniques involve local voice-assisted troubleshooting the cloud-based voice assistant service. Other techniques relate to interactions between local and cloud-based processing of voice inputs on a device that supports both local and cloud-based processing.

Abstract: As noted above, example techniques relate to toggling a cloud-based VAS between enabled and disabled modes. An example implementation involves a NMD detecting that the housing is in a first orientation and enabling a first mode. Enabling the first mode includes disabling voice input processing via a cloud-based VAS and enabling local voice input processing. In the first mode, the NMD captures sound data associated with a first voice input and detects, via a local natural language unit, that the first voice input comprises sound data matching one or more keywords. The NMD determines an intent of the first voice input and performs a first command according to the determined intent. The NMD may detect that the housing is in a second orientation and enables the second mode. Enabling the second mode includes enabling voice input processing via the cloud-based VAS.

Abstract: In one aspect, a playback device includes a voice assistant service (VAS) wake-word engine and a command keyword engine. The playback device detects, via the command keyword engine, a first command keyword of in voice input of sound detected by one or more microphones of the playback device. The playback device determines an intent based on at least one keyword in the voice input via a local natural language unit (NLU). After detecting the first command keyword event and determining the intent, the playback device performs a first playback command corresponding to the first command keyword and according to the determined intent. When the playback device detects, via the wake-word engine, a wake-word in voice input, the playback device streams sound data corresponding to at least a portion of the voice input to one or more remote servers associated with the VAS.

Abstract: A server transmits an encoded game frame over a network to a respective client system as a set of packets. In response to transmitting the set of packets, the server determines a bandwidth estimate based on the size of the encoded game frame and the timing data associated with the transmitted set of packets. The server then compares the bandwidth estimate to a current video bitrate of the game stream being transmitted from the server to the respective client device. In response to the comparison indicating an underutilization of the network, the server increases the encoding bitrate. Further, in response to the comparison indication an overutilization of the network, the server decreases the encoding bitrate.

Abstract: In one aspect, a playback device includes a voice assistant service (VAS) wake-word engine and a command keyword engine. The playback device detects, via the command keyword engine, a first command keyword, and determines whether one or more playback conditions corresponding to the first command keyword are satisfied. Based on (a) detecting the first command keyword and (b) determining that the one or more playback conditions corresponding to the first command keyword are satisfied, the playback device playback device performs a first playback command corresponding to the first command keyword. When the playback device detects, via the wake-word engine, a wake-word in voice input, the playback device streams sound data corresponding to at least a portion of the voice input to one or more remote servers associated with the VAS.

Abstract: In one aspect, a playback device includes a voice assistant service (VAS) wake-word engine and a command keyword engine. The playback device detects, via the command keyword engine, a first command keyword, and determines whether one or more playback conditions corresponding to the first command keyword are satisfied. Based on (a) detecting the first command keyword and (b) determining that the one or more playback conditions corresponding to the first command keyword are satisfied, the playback device playback device performs a first playback command corresponding to the first command keyword. When the playback device detects, via the wake-word engine, a wake-word in voice input, the playback device streams sound data corresponding to at least a portion of the voice input to one or more remote servers associated with the VAS.

Abstract: In one aspect, a playback device includes a voice assistant service (VAS) wake-word engine and a command keyword engine. The playback device detects, via the command keyword engine, a first command keyword of in voice input of sound detected by one or more microphones of the playback device. The playback device determines an intent based on at least one keyword in the voice input via a local natural language unit (NLU). After detecting the first command keyword event and determining the intent, the playback device performs a first playback command corresponding to the first command keyword and according to the determined intent. When the playback device detects, via the wake-word engine, a wake-word in voice input, the playback device streams sound data corresponding to at least a portion of the voice input to one or more remote servers associated with the VAS.

Abstract: As noted above, example techniques relate to toggling a cloud-based VAS between enabled and disabled modes. An example implementation involves a NMD detecting that the housing is in a first orientation and enabling a first mode. Enabling the first mode includes disabling voice input processing via a cloud-based VAS and enabling local voice input processing. In the first mode, the NMD captures sound data associated with a first voice input and detects, via a local natural language unit, that the first voice input comprises sound data matching one or more keywords. The NMD determines an intent of the first voice input and performs a first command according to the determined intent. The NMD may detect that the housing is in a second orientation and enables the second mode. Enabling the second mode includes enabling voice input processing via the cloud-based VAS.

Abstract: As noted above, example techniques relate to offline voice control. A local voice input engine may process voice inputs locally when processing voice inputs via a cloud-based voice assistant service is not possible. Some techniques involve local (on-device) voice-assisted set-up of a cloud-based voice assistant service. Further example techniques involve local voice-assisted troubleshooting the cloud-based voice assistant service. Other techniques relate to interactions between local and cloud-based processing of voice inputs on a device that supports both local and cloud-based processing.

Abstract: In one aspect, a playback device includes at least one microphone configured to detect sound. The playback detects sound via the one or more microphones and determines whether (i) the detected sound includes a voice input, (ii) the detected sound excludes background speech, and (iii) the voice input includes a command keyword. In response to the determining, the playback device performs a playback function corresponding to the command keyword.

Abstract: As noted above, example techniques relate to offline voice control. A local voice input engine may process voice inputs locally when processing voice inputs via a cloud-based voice assistant service is not possible. Some techniques involve local (on-device) voice-assisted set-up of a cloud-based voice assistant service. Further example techniques involve local voice-assisted troubleshooting the cloud-based voice assistant service. Other techniques relate to interactions between local and cloud-based processing of voice inputs on a device that supports both local and cloud-based processing.

Abstract: In one aspect, a playback device includes a voice assistant service (VAS) wake-word engine and a command keyword engine. The playback device detects, via the command keyword engine, a first command keyword of in voice input of sound detected by one or more microphones of the playback device. The playback device determines an intent based on at least one keyword in the voice input via a local natural language unit (NLU). After detecting the first command keyword event and determining the intent, the playback device performs a first playback command corresponding to the first command keyword and according to the determined intent. When the playback device detects, via the wake-word engine, a wake-word in voice input, the playback device streams sound data corresponding to at least a portion of the voice input to one or more remote servers associated with the VAS.

Abstract: As noted above, example techniques relate to toggling a cloud-based VAS between enabled and disabled modes. An example implementation involves a NMD detecting that the housing is in a first orientation and enabling a first mode. Enabling the first mode includes disabling voice input processing via a cloud-based VAS and enabling local voice input processing. In the first mode, the NMD captures sound data associated with a first voice input and detects, via a local natural language unit, that the first voice input comprises sound data matching one or more keywords. The NMD determines an intent of the first voice input and performs a first command according to the determined intent. The NMD may detect that the housing is in a second orientation and enables the second mode. Enabling the second mode includes enabling voice input processing via the cloud-based VAS.

Abstract: As noted above, example techniques relate to offline voice control. A local voice input engine may process voice inputs locally when processing voice inputs via a cloud-based voice assistant service is not possible. Some techniques involve local (on-device) voice-assisted set-up of a cloud-based voice assistant service. Further example techniques involve local voice-assisted troubleshooting the cloud-based voice assistant service. Other techniques relate to interactions between local and cloud-based processing of voice inputs on a device that supports both local and cloud-based processing.

Abstract: As noted above, example techniques relate to toggling a cloud-based VAS between enabled and disabled modes. An example implementation involves a NMD detecting that the housing is in a first orientation and enabling a first mode. Enabling the first mode includes disabling voice input processing via a cloud-based VAS and enabling local voice input processing. In the first mode, the NMD captures sound data associated with a first voice input and detects, via a local natural language unit, that the first voice input comprises sound data matching one or more keywords. The NMD determines an intent of the first voice input and performs a first command according to the determined intent. The NMD may detect that the housing is in a second orientation and enables the second mode. Enabling the second mode includes enabling voice input processing via the cloud-based VAS.