Patent classifications
G10L13/00
TECHNIQUES TO PROVIDE SENSITIVE INFORMATION OVER A VOICE CONNECTION
Embodiments may generally be directed components and techniques to detect a request to provide banking account information over a one or more voice connections, identify the requested banking account information, and generate speech data representing the banking account information requested. In embodiments further include communicating the speech data to another device.
TECHNIQUES TO PROVIDE SENSITIVE INFORMATION OVER A VOICE CONNECTION
Embodiments may generally be directed components and techniques to detect a request to provide banking account information over a one or more voice connections, identify the requested banking account information, and generate speech data representing the banking account information requested. In embodiments further include communicating the speech data to another device.
ELECTRONIC DEVICE AND METHOD OF CONTROLLING THEREOF
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.
ELECTRONIC DEVICE AND METHOD OF CONTROLLING THEREOF
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.
PROCESSING ACCELERATOR ARCHITECTURES
In various embodiments, this application provides an audio information processing method, an audio information processing apparatus, an electronic device, and a storage medium. An audio information processing method in an embodiment includes: obtaining a first audio feature corresponding to audio information; performing, based on an audio feature at a specified moment in the first audio feature and audio features adjacent to the audio feature at the specified moment, an encoding on the audio feature at the specified moment to obtain a second audio feature corresponding to the audio information; obtaining decoded text information corresponding to the audio information; and obtaining, based on the second audio features and the decoded text information, text information corresponding to the audio information. According to this method, fewer parameters are used in the process of obtaining the second audio feature and obtaining, based on the second audio feature and the decoded text information, the text information corresponding to the audio information, thereby reducing computational complexity in the audio information processing process and improving audio information processing efficiency.
PROCESSING ACCELERATOR ARCHITECTURES
In various embodiments, this application provides an audio information processing method, an audio information processing apparatus, an electronic device, and a storage medium. An audio information processing method in an embodiment includes: obtaining a first audio feature corresponding to audio information; performing, based on an audio feature at a specified moment in the first audio feature and audio features adjacent to the audio feature at the specified moment, an encoding on the audio feature at the specified moment to obtain a second audio feature corresponding to the audio information; obtaining decoded text information corresponding to the audio information; and obtaining, based on the second audio features and the decoded text information, text information corresponding to the audio information. According to this method, fewer parameters are used in the process of obtaining the second audio feature and obtaining, based on the second audio feature and the decoded text information, the text information corresponding to the audio information, thereby reducing computational complexity in the audio information processing process and improving audio information processing efficiency.
Query rephrasing using encoder neural network and decoder neural network
A method comprising receiving first data representative of a query. A representation of the query is generated using an encoder neural network and the first data. Words for a rephrased version of the query are selected from a set of words comprising a first subset of words comprising words of the query and a second subset of words comprising words absent from the query. Second data representative of the rephrased version of the query is generated.
Query rephrasing using encoder neural network and decoder neural network
A method comprising receiving first data representative of a query. A representation of the query is generated using an encoder neural network and the first data. Words for a rephrased version of the query are selected from a set of words comprising a first subset of words comprising words of the query and a second subset of words comprising words absent from the query. Second data representative of the rephrased version of the query is generated.
Task resumption in a natural understanding system
A speech-processing system may provide access to one or more skills via spoken commands and/or responses in the form of synthesized speech. The system may be capable of keeping one or more skills active in the background while a user interacts (e.g., provides inputs to and/or receives outputs from) with a skill running in the foreground. A background skill may receive some trigger data, and determine to request the system to return the background skill to the foreground to, for example, request a user input regarding an action previously requested by the user. In some cases, the user may invoke a background skill to continue a previous interaction. The system may return the background skill to the foreground. The resumed skill may continue a previous interaction to, for example, to query the user for instructions, provide an update or alert, or continue a previous output.
Task resumption in a natural understanding system
A speech-processing system may provide access to one or more skills via spoken commands and/or responses in the form of synthesized speech. The system may be capable of keeping one or more skills active in the background while a user interacts (e.g., provides inputs to and/or receives outputs from) with a skill running in the foreground. A background skill may receive some trigger data, and determine to request the system to return the background skill to the foreground to, for example, request a user input regarding an action previously requested by the user. In some cases, the user may invoke a background skill to continue a previous interaction. The system may return the background skill to the foreground. The resumed skill may continue a previous interaction to, for example, to query the user for instructions, provide an update or alert, or continue a previous output.