An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

The various methods and devices described herein relate to devices which, in at least certain embodiments, may include one or more sensors for providing data relating to user activity and at least one processor for causing the device to respond based on the user activity which was determined, at least in part, through the sensors. The response by the device may include a change of state of the device, and the response may be automatically performed after the user activity is determined.

Automated Response to and Sensing of User Activity in Portable Devices

A virtual assistant uses context information to supplement natural language or gestural input from a user. Context helps to clarify the user's intent and to reduce the number of candidate interpretations of the user's input, and reduces the need for the user to provide excessive clarification input. Context can include any available information that is usable by the assistant to supplement explicit user input to constrain an information-processing problem and/or to personalize results. Context can be used to constrain solutions during various phases of processing, including, for example, speech recognition, natural language processing, task flow processing, and dialog generation.

Using context information to facilitate processing of commands in a virtual assistant

A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

System and method for a cooperative conversational voice user interface

A method and apparatus are provided for building an intelligent automated assistant. Embodiments of the present invention rely on the concept of “active ontologies” (e.g., execution environments constructed in an ontology-like manner) to build and run applications for use by intelligent automated assistants. In one specific embodiment, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontology includes at least one active processing element that models a domain. At least one of the remote services is then registered for use in the domain.

Method and apparatus for building an intelligent automated assistant

A data structure is provided for annotating data files within a database. The annotation data comprises a phoneme and word lattice which allows the quick and efficient searching of data files within the database in response to a user's input query. The structure of the annotation data is such that it allows the input query to be made by voice and can be used for annotating various kinds of data files, such as audio data files, video data files, multimedia data files etc. The annotation data may be generated from the data files themselves or may be input by the user either from a voiced input or from a typed input.

Database annotation and retrieval

A dynamic programming technique is provided for matching two sequences of phonemes both of which may be generated from text or speech. The scoring of the dynamic programming matching technique uses phoneme confusion scores, phoneme insertion scores and phoneme deletion scores which are obtained in advance in a training session and, if appropriate, confidence data generated by a recognition system if the sequences are generated from speech.

Language recognition using a similarity measure

A system is provided for matching two or more sequences of phonemes both or all of which may be generated from text or speech. A dynamic programming matching technique is preferably used having constraints which depend upon whether or not the two sequences are generated from text or speech and in which the scoring of the dynamic programming paths is weighted by phoneme confusion scores, phoneme insertion scores and phoneme deletion scores where appropriate.

Pattern matching method and apparatus

A system is provided for comparing an input query with a number of stored annotations to identify information to be retrieved from a database. The comparison technique divides the input query into a number of fixed-size fragments and identifies how many times each of the fragments occurs within each annotation using a dynamic programming matching technique. The frequencies of occurrence of the fragments in both the query and the annotation are then compared to provide a measure of the similarity between the query and the annotation. The information to be retrieved is then determined from the similarity measures obtained for all the annotations.

Language recognition using sequence frequency

The data structure is used in accessing a plurality of data files. The data stucture comprises a plurality of annotation storage areas adapted to correspond with the data files, each annotation storage area containing an annotation an annotation representing a time sequential signal and each annotation storage area comprising a plurality of block storage areas each containing phoneme and word data forming a respective temporal block of the annotation and each block having an associated time index identifying a timing of the block within the corresponding annotation. Each block storage area includes a plurality of node storage areas, each asociated with a node which represents a point in time at which a word and/or phoneme begins or ends within the corresponding annotation, and each node storage area having a time offset storage area containing a time offset defining the point in time represented by the node relative to the time index associated with the corresponding block. Each node storage area further has one or more phoneme link storage areas, each having a phoneme storage area containing data identifying a phoneme associated with corresponding node; or one or more word link storage areas, each having a word storage area containing data identifying a word associated with the corresponding node. One or more of the node storage areas has at least one of the phoneme link storage areas and at least one of the word link storage areas.

Jason Peter Andrew Charlesworth

Papers

Database annotation and retrieval

Language recognition using a similarity measure

Pattern matching method and apparatus

Language recognition using sequence frequency

Database annotation and retrieval including phoneme data