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

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 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

The method includes automatically, without user input and without regard to whether a digital assistant application has been separately invoked by a user, determining that the electronic device is in a vehicle. In some implementations, determining that the electronic device is in a vehicle comprises detecting that the electronic device is in communication with the vehicle (e.g., via a wired or wireless communication techniques and/or protocols). The method also includes, responsive to the determining, invoking a listening mode of a virtual assistant implemented by the electronic device. In some implementations, the method also includes limiting the ability of a user to view visual output presented by the electronic device, provide typed input to the electronic device, and the like.

Automatically adapting user interfaces for hands-free interaction

A method for operating a voice trigger is provided. In some implementations, the method is performed at an electronic device including one or more processors and memory storing instructions for execution by the one or more processors. The method includes receiving a sound input. The sound input may correspond to a spoken word or phrase, or a portion thereof. The method includes determining whether at least a portion of the sound input corresponds to a predetermined type of sound, such as a human voice. The method includes, upon a determination that at least a portion of the sound input corresponds to the predetermined type, determining whether the sound input includes predetermined content, such as a predetermined trigger word or phrase. The method also includes, upon a determination that the sound input includes the predetermined content, initiating a speech-based service, such as a voice-based digital assistant.

Voice trigger for a digital assistant

Time-scaled, sound signals (i.e. sounds output at differing speeds) are generated by mixing weighted time-and frequency-domain processed signals, the former signal generally representing speech-based signals while the latter representing music-based signals. The weights applied to each type of signal may be determined by a scaling factor, which in turn is related to the desired speed at which a listener desires to hear a sound signal. In one example of the invention, only stationary signal portions of an input sound signal are used to generate time-scaled processed signals. An adaptive frame-size may also be used to pre-process the separate signals prior to being weighted, which at least decreases the amount of unwanted reverberative sound qualities in a resulting sound signal. Together, techniques envisioned by the present invention produce improved, speed adjusted sound signals.

Methods and devices for selectively generating time-scaled sound signals

Methods and systems for a mixed time-frequency domain compander, where the expander and compressor are applied in the frequency domain (subbands), while the limiter and the linear gain are applied in the time-domain (full band). Far-end noise reduction is achieved by adapting the expander gain to the far-end noise, near-end noise compensation is achieved by adapting the linear gain and the compressor gain to the near-end noise. The range of the linear gain section is set individually for each subband, but the linear gain is essentially applied to the full band signal via a scaling procedure. The scaling procedure first reduces the compander gain in the frequency domain by a scaling factor and then performs the reciprocal reverse scaling in the time domain. Far-end noise reduction is coupled to near-end noise compensation in order to avoid cross-modulation of the far-end noise by the near-end noise.

Systems and methods for far-end noise reduction and near-end noise compensation in a mixed time-frequency domain compander to improve signal quality in communications systems

A method and apparatus for enabling an improved experience by better matching of the auditory space to the visual space in video viewing applications such as those that may be used in video teleconferencing systems and in the viewing of videos with associated audio (e.g., movies). In one embodiment, a viewer's location and head position relative to a video display screen is determined, one or more desired sound source locations (which may, for example, be related to a projection on the video display) are determined, and binaural stereo audio signals which accurately locate the sound sources at the desired sound source locations are advantageously generated.

Method and apparatus for improved matching of auditory space to visual space in video viewing applications

A method and apparatus for enabling an improved experience by better matching of the auditory space to the visual space in video viewing applications such as those that may be used in video teleconferencing systems using window-based displays. In particular, in accordance with certain illustrative embodiments of the present invention, one or more desired sound source locations are determined based on a location of a window in a video teleconference display device (which may, for example, comprise the image of a teleconference participant within the given window), and a plurality of audio signals which accurately locate the sound sources at the desired sound source locations (based on the location of the given window in the display) are advantageously generated.

Method and apparatus for improved mactching of auditory space to visual space in video teleconferencing applications using window-based displays

A receiver for receiving wireless packetized audio signals having packet headers, and packet payloads including encoded audio signals is provided. The receiver includes an audio decoder for decoding the encoded audio signals into digital audio signals, an audio error detector for detecting impulsive noise in the digital audio signals caused by corrupted payload packets, and a digital signal restoration unit for removing the impulsive noise from the digital audio signals. Further, a method of noise reduction includes the steps of receiving radio frequency packetized audio signals having packet headers, and packet payloads including encoded audio signals and demodulating the RF signals. The method further includes decoding the encoded audio signals into digital audio signals and detecting impulsive noise in the digital audio signals caused by corrupted payload packets. The method further includes removing the impulsive noise by reconstructing the corrupted digital audio signal.

System and method of noise reduction in receiving wireless transmission of packetized audio signals

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Walter Etter

Author Tools

Chat about Author