Apple Inc.

Henry Graham Mason

Matthias Paulik

Freddy Allen Anzures

Lucas Christopher Newman

Jason A Skinder

Thomas M Alsina

Gregory R Chapman

Neil Gareth Crane

Thomas Brogan Duffy

Matthew G Waston

Joseph Sokol

Eric Albert

Scott James Forstall

Gregory B Novick

Cahya Adiansyah Masputra

John Joseph Iarocci

Gordon J Freedman

Edward T Schmidt

Nitin Ganatra

Richard Warren Schreyer

Christopher R Wysocki

Anumita Biswas

Sachin S Kajarekar

Damien Pascal Sorresso

Lucia Elena Ballard

Darren S Litzinger

Christopher Marcellino

Curtis Rothert

Shaun Eric Williams

Nicolas Zeitlin

Charles Srisuwananukorn

Michael Van Milligan

David B Myszewski

Matthew S Seigel

Karric Kwong

David William Goodwin

Ali S Mohamed

Neha Agrawal

Mahesh Krishnamoorthy

Sinan Akay

Selen Uguroglu

Saravana Kumar Rathinam

Thomas G Adcox

Damien Sorresso

Richard Schreyer

David Myszewski

Cahya Masputra

Darren Litzinger

Lucia Ballard

Scott Forstall

John Iarocci

Gregory Novick

Systems and processes for providing user-specific acoustic models are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a plurality of speech inputs, each of the speech inputs associated with a same user of the electronic device; providing each of the plurality of speech inputs to a user-independent acoustic model, the user-independent acoustic model providing a plurality of speech results based on the plurality of speech inputs; initiating a user-specific acoustic model on the electronic device; and adjusting the user-specific acoustic model based on the plurality of speech inputs and the plurality of speech results.

User-specific acoustic models

A computer system receives information snippets from a mobile device. The information snippets are extracted from a simulcast of a data stream of a radio broadcast received on the mobile device. The system identifies content metadata from the information snippets. The content metadata describes one or more features of the radio broadcast. The system selects a radio station from a radio station repository based on attributes of the radio station. One of the selection criteria is that the attributes of the radio station match at least a portion of the content metadata. The system presents a reference to the radio station to the mobile device as a recommendation.

Content selection based on simulcast data

Systems and processes for performing a task with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a natural-language input; determining, based on the natural-language input, a first task and first usefulness score associated with the first task; receiving, from another electronic device, a second task and second usefulness score associated with the second task; determining whether the first usefulness score is higher than the second usefulness score; in accordance with a determination that the first usefulness score is higher than the second usefulness score: performing the first task determined by the electronic device; and providing an output indicating whether the first task has been performed; and in accordance with a determination that the second usefulness score is higher than the first usefulness score: performing the second task received from the another electronic device; and providing an output indicating whether the second task has been performed.

Offline personal assistant

The present disclosure generally relates to context-based endpoint detection in user speech input. A method for identifying an endpoint of a spoken request by a user may include receiving user input of natural language speech including one or more words; identifying at least one context associated with the user input; generating a probability, based on the at least one context associated with the user input, that a location in the user input is an endpoint; determining whether the probability is greater than a threshold; and in accordance with a determination that the probability is greater than the threshold, identifying the location in the user input as the endpoint.

Context-based endpoint detection

Systems and processes for evaluating embedded personalized systems are provided. In one example process, instructions that define an experiment associated with a personalized speech recognition system can be received. The instructions can define one or more experimental parameters. In accordance with the received instructions, a second personalized speech recognition system can be generated based on the personalized speech recognition system and the one or more experimental parameters. Additionally, the plurality of user speech samples can be processed using the second personalized speech recognition system to generate a plurality of speech recognition results and a plurality of accuracy scores corresponding to the plurality of speech recognition results. Second instructions can be received based on the plurality of accuracy scores. In accordance with the second instructions, the second speech recognition system can be activated.

Privacy preserving distributed evaluation framework for embedded personalized systems

Systems and processes for analyzing audio input for efficient speech and music recognition are provided. In one example process, an audio input can be received. A determination can be made as to whether the audio input includes music. In addition, a determination can be made as to whether the audio input includes speech. In response to determining that the audio input includes music, an acoustic fingerprint representing a portion of the audio input that includes music is generated. In response to determining that the audio input includes speech rather than music, an end-point of a speech utterance of the audio input is identified.

Analyzing audio input for efficient speech and music recognition

A host devices transfers client data from a client device to the host device. The host device generates sort keys for host data that includes the client data. The host device sorts the host data using the sort keys and transfers the sorted host data to the client device. The client data and host data may include music, video, or other content.

Partial sort on a host

Operating a radio receiver can include identifying a set of stations that broadcast a radio program using different frequencies or different transmission protocols at substantially the same time. Broadcast signal strength, or some other signal quality metric, of broadcast signals from the stations can be evaluated, and the radio receiver can be tuned to one of the stations in the set of stations based on the evaluation.

Radio receiver

A mobile device receives a radio simulcast of streaming data and content. The mobile device extracts metadata from the radio simulcast. The mobile device identifies a communication channel to a content provider by comparing components of the metadata with reference data. The mobile device presents a user interface for connecting to the content provider through the communication channel. The mobile device also records the metadata with a time stamp and provides a user interface for displaying the data and time of content received.

Processing simulcast data

Metadata is synchronized between a mobile device and a remote node over a first network, where the metadata specifies media content to be synchronized between the mobile device and the remote node. Subsequently a network connection is established with the remote node over a second network. The media content is bi-directionally synchronized between the mobile device and the remote node over the second network based on the metadata that was synchronized over the first network.

Dual-phase content synchronization

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San Francisco, CA, United States of America

Henry Graham Mason