The present invention relates to a system for retrieving information from a network such as the Internet. A user creates a user-defined record in a database that identifies an information source, such as a web site, containing information of interest to the user. This record identifies the location of the information source and also contains a recognition grammar based upon a speech command assigned by the user. Upon receiving the speech command from the user that is described within the recognition grammar, a network interface system accesses the information source and retrieves the information requested by the user.

The present invention relates to a system for retrieving information from a network such as the Internet. A user creates a user-defined record in a database that identifies an information source, such as a web site, containing information of interest to the user. This record identifies the location of the information source and also contains a recognition grammar based upon a speech command assigned by the user. Upon receiving the speech command from the user that is described within the recognition grammar, a network interface system accesses the information source and retrieves the information requested by the user.

Techniques for selecting an emotion type code associated with semantic content in an interactive dialog system. In an aspect, fact or profile inputs are provided to an emotion classification algorithm, which selects an emotion type based on the specific combination of fact or profile inputs. The emotion classification algorithm may be rules-based or derived from machine learning. A previous user input may be further specified as input to the emotion classification algorithm. The techniques are especially applicable in mobile communications devices such as smartphones, wherein the fact or profile inputs may be derived from usage of the diverse function set of the device, including online access, text or voice communications, scheduling functions, etc.

Techniques for selecting an emotion type code associated with semantic content in an interactive dialog system. In an aspect, fact or profile inputs are provided to an emotion classification algorithm, which selects an emotion type based on the specific combination of fact or profile inputs. The emotion classification algorithm may be rules-based or derived from machine learning. A previous user input may be further specified as input to the emotion classification algorithm. The techniques are especially applicable in mobile communications devices such as smartphones, wherein the fact or profile inputs may be derived from usage of the diverse function set of the device, including online access, text or voice communications, scheduling functions, etc.

Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

An operation method for a mobile electronic device is provided. The operation method includes: transmitting a calling phone number to a wireless audio product from an operation system of the mobile electronic device via wireless communication, wherein the mobile electronic device is wirelessly connected to the wireless audio product; transmitting the calling phone number to an application software of the mobile electronic device by the wireless audio product; searching a caller name corresponding to the calling phone number by the application software of the mobile electronic device; transmitting the caller name to the wireless audio product by the application software of the mobile electronic device via wireless communication; and playing the caller name by the wireless audio product.

An operation method for a mobile electronic device is provided. The operation method includes: transmitting a calling phone number to a wireless audio product from an operation system of the mobile electronic device via wireless communication, wherein the mobile electronic device is wirelessly connected to the wireless audio product; transmitting the calling phone number to an application software of the mobile electronic device by the wireless audio product; searching a caller name corresponding to the calling phone number by the application software of the mobile electronic device; transmitting the caller name to the wireless audio product by the application software of the mobile electronic device via wireless communication; and playing the caller name by the wireless audio product.

A voice command-driven system and computer-implemented method are disclosed for selecting a data item in a list of text-based data items stored in a database using a simple affirmative voice command input without utilizing a connection to a network. The text-based data items in the list are converted to speech using an embedded text-to-speech engine and an audio output of a first converted data item is provided. A listening state is entered into for a predefined pause time to await receipt of the simple affirmative voice command input. If the simple affirmative voice command input is received during the predefined pause time, the first converted data item is selected for processing. If the simple affirmative voice command input is not received during the predefined pause time, an audio output of a next converted data item in the list is provided.

A voice command-driven system and computer-implemented method are disclosed for selecting a data item in a list of text-based data items stored in a database using a simple affirmative voice command input without utilizing a connection to a network. The text-based data items in the list are converted to speech using an embedded text-to-speech engine and an audio output of a first converted data item is provided. A listening state is entered into for a predefined pause time to await receipt of the simple affirmative voice command input. If the simple affirmative voice command input is received during the predefined pause time, the first converted data item is selected for processing. If the simple affirmative voice command input is not received during the predefined pause time, an audio output of a next converted data item in the list is provided.