A system for and method of characterizing a target application acoustic domain analyzes one or more speech data samples from the target application acoustic domain to determine one or more target acoustic characteristics, including a CODEC type and bit-rate associated with the speech data samples. The determined target acoustic characteristics may also include other aspects of the target speech data samples such as sampling frequency, active bandwidth, noise level, reverberation level, clipping level, and speaking rate. The determined target acoustic characteristics are stored in a memory as a target acoustic data profile. The data profile may be used to select and/or modify one or more out of domain speech samples based on the one or more target acoustic characteristics.

A voice assistance system is described, comprising a microphone, a processor with memory instructions configured to receive an audio input of at least one user from the microphone to identify at least one object associated with a symbol of a database, determine the preferred language associated with the symbol, transmit a wireless signal to at least one smart device, this smart device being able to interact with an object associated with a database symbol, either through a signal managed by an infrared ray activation module, and by means of a signal managed by an activation module housed in electrical derivation boxes, a power transistor providing to drive a classic relay connected to the object associated with the database symbol, such system comprising at least one further microphone, at least one further processor with memory instructions configured to receive an input put audio, and an additional loudspeaker.

Disclosed is a portable communication device, including a display, at least one microphone, a memory, and a processor operably connected to the display, the at least one microphone and the memory, wherein the processor is configured to display guide information, via the display, in response to a user input, the guide information including a first display object related to guide a user voice input for generation of a new voice command and a second display object related to at least one application executed by the new voice command via the portable communication device, receive audio data corresponding to the first display object from a user through the at least one microphone, generate the new voice command corresponding to the audio data, and store, in the memory, the new voice command corresponding to the received audio data and mapping information indicating that the new voice command and the at least one application are mapped.

Disclosed is a portable communication device, including a display, at least one microphone, a memory, and a processor operably connected to the display, the at least one microphone and the memory, wherein the processor is configured to display guide information, via the display, in response to a user input, the guide information including a first display object related to guide a user voice input for generation of a new voice command and a second display object related to at least one application executed by the new voice command via the portable communication device, receive audio data corresponding to the first display object from a user through the at least one microphone, generate the new voice command corresponding to the audio data, and store, in the memory, the new voice command corresponding to the received audio data and mapping information indicating that the new voice command and the at least one application are mapped.

The subject matter of this specification can be embodied in, among other things, a method that includes receiving geographical information derived from a non-verbal user action associated with a first computing device. The non-verbal user action implies an interest of a user in a geographic location. The method also includes identifying a grammar associated with the geographic location using the derived geographical information and outputting a grammar indicator for use in selecting the identified grammar for voice recognition processing of vocal input from the user.

A method includes receiving user queries directed toward a cloud-based assistant service. For each received user query directed toward the cloud-based assistant service, the method also includes extracting one or more attributes from the user query and logging the user query into one or more of a plurality of category buckets based on the one or more attributes extracted from the user query. The method also includes determining when at least one of the plurality of category buckets includes a threshold number of the user queries logged into the at least one category bucket, and when the at least one of the plurality of category buckets includes the threshold number of the user queries, generating a distilled model of the cloud-based assistant service. The distilled model of the cloud-based assistant service is configured to execute on one or more target client devices.

A method includes receiving user queries directed toward a cloud-based assistant service. For each received user query directed toward the cloud-based assistant service, the method also includes extracting one or more attributes from the user query and logging the user query into one or more of a plurality of category buckets based on the one or more attributes extracted from the user query. The method also includes determining when at least one of the plurality of category buckets includes a threshold number of the user queries logged into the at least one category bucket, and when the at least one of the plurality of category buckets includes the threshold number of the user queries, generating a distilled model of the cloud-based assistant service. The distilled model of the cloud-based assistant service is configured to execute on one or more target client devices.

Methods and systems for dynamically updating machine learning models that provide conversational responses through the use of a configuration file that defines modifications and changes to the machine learning model are disclosed. For example, the configuration file may be used to define an expected behavior and required attributes for instituting modifications and changes (e.g., via a mutation algorithm) to the machine learning model.

Methods and systems for dynamically updating machine learning models that provide conversational responses through the use of a configuration file that defines modifications and changes to the machine learning model are disclosed. For example, the configuration file may be used to define an expected behavior and required attributes for instituting modifications and changes (e.g., via a mutation algorithm) to the machine learning model.

Systems and methods for a media guidance application that generates results in multiple languages for search queries. In particular, the media guidance application resolves multiple language barriers by taking automatic and manual user language settings and applying those settings to a variety of potential search results.