An electronic apparatus includes: a memory storing one or more commands; and a processor connected to the memory and configured to control the electronic apparatus, wherein the processor is configured, by executing the one or more instructions, to: identify a first intention word and a first target word from first speech, acquire second speech received after the first speech based on at least one of the identified first intention word or the identified first target word not matching a word stored in the memory, acquire a similarity between the first speech and the second speech, and acquire response information based on the first speech and the second speech based on the similarity being a threshold value or more.

Systems, methods, and non-transitory, machine-readable media to facilitate updating media devices in a local network with a client-server architecture are disclosed. A primary media device may be configured to operate as a server in a local network, receive audio/video (A/V) content via an Internet connection and/or a satellite network connection, serve the A/V content to a set of one or more secondary media devices for display with at least one television of a set of one or more televisions, and receive a set of one or more software updates via the Internet connection, a Universal Serial Bus (USB) connection, and/or the satellite network connection. One or more software updates of the set of one or more software updates may be specified for, and may be transferred to, the set of one or more secondary media devices.

Disclosed is an electronic device. The electronic device may execute an application for transmitting and receiving at least one of text data or voice data with another electronic device using the communication module, in response to occurrence of at least one event, based on receiving at least one of text data or voice data from the another electronic device, identify that a confirmation is necessary using the digital assistant based on at least one of text data or voice data being generated based on a characteristic of ab utterance using a digital assistant, generate a notification to request confirmation using the digital assistant based on confirmation being necessary, and output the notification using the application.

A method for identifying that a confirmation is necessary may include identifying using voice data or text data that is received from another electronic device using a rule-based or AI algorithm.

When a confirmation is necessary is identified using the AI algorithm, the method may use machine learning, neural network, or a deep learning algorithm.

This application provides an audio output method and a terminal device. The method helps to reduce the operation complexity of a user, improve a degree of intelligence of the terminal device, and finally improve the user experience. The method includes that: a second terminal device may send an audio output request to a first terminal device, and a user may operate the first terminal device or an audio output device connected to the first terminal device, to trigger the second terminal device to obtain audio data corresponding to the audio output request. When the audio output device is a wireless audio output device, the second terminal device may establish a communication link with the wireless audio output device, to control the wireless audio output device to output a first audio signal corresponding to the audio data; and when the audio output device is a wired audio output device, the first terminal device may obtain audio data from the second terminal device, to control the audio output device connected to the first terminal device to output a first audio signal corresponding to the audio data.

An in-vehicle speech interaction method and a device are provided. The method includes: obtaining user speech information; determining a user instruction based on the user speech information; determining, based on the user instruction, whether response content to the user instruction is privacy-related; and determining, based on whether the response content is privacy-related, whether to output the response content in a privacy protection mode, to protect privacy from being leaked.

An audio sample including speech and ambient sounds is transmitted to a vehicle computer. Recorded audio is received from the vehicle computer, the recorded audio including the audio sample broadcast by the vehicle computer and recorded by the vehicle computer and recognized speech from the recorded audio. The recognized speech and text of the speech are input to a machine learning program that outputs whether the recognized speech matches the text. When the output from the machine learning program indicates that the recognized speech does not match the text, the recognized speech and the text are included in a training dataset for the machine learning program.

Systems, methods, and non-transitory, machine-readable media to facilitate streaming in a local network are disclosed. A primary media device may be configured to: operate as a server in a local network, receive audio/video (A/V) content, and provide the A/V content to a first display. A secondary media device may be communicatively connected to the primary media device and may be configured to: operate as a client with respect to the primary media device in the local network, receive the A/V content from the primary media device, and provide the A/V content to a second display. The primary media device and the secondary media device may use multiple subnets in the local network. The primary media device and/or the secondary media device may select a first subnet of the multiple subnets to use based at least in part on a type of content to communicate via the first subnet.

Implementations relate to proactively aggregating client device data to append to client assistant data that is communicated to a server device in response to a user request to a client automated assistant. When a user request that is associated with, for example, a peripheral client device, is received at a client device, the client device can communicate, to a server device, data that embodies the user request (e.g., audio data and/or local speech recognition data), along with peripheral device data that was received before the client device received the user request. In this way, the client automated assistant can bypass expressly soliciting peripheral device data each time a user request is received at another client device. Instead, a peripheral device can proactively communicate device data to a client device so that the device data can be appended to request data communicated to the server device from a particular client device.

A voice control system for recreational vehicles controls safe operation of deployable components of the RV, such as an antenna, awning or room extension. A voice recognition system is employed to interpret voice commands and control operation of the deployable components in response. A control system monitors the status of the RV and its components to detect unsafe conditions relating to operation of the deployable components. For example, this can be done via a wired or wireless network of sensors detecting the state of the RV and its deployable components. The control system can also monitor the status of the RV via the data bus built into the RV. If an unsafe condition is detected, the safety manager of the control system triggers a warning or activates a predetermined interlock to prevent unsafe operation of the RV and its deployable components.

Disambiguating question answering responses by receiving voice command data associated with a first user, determining a first user identity according to the first user voice command data, determining a first user activity context according to the first user voice command data, determining a first response for the first user, receiving voice command data associated with a second user, determining a second user identity according to the second user voice command data, determining a second user activity context according to the second user voice command data, determining a second response for the second user, determining a predicted ambiguity between the first response and the second response, altering the first response according to the predicted ambiguity, and providing the first response and the second response.