Intel Corporation

David Pearce

Tobias Bocklet

Gokcen Cilingir

Paulo Lopez Meyer

Wesley Hamilton Smith

Adam Kupryjanow

Karl I Nordling

Amir Hindie

Karl Leinfelder

Jim Beaney

Suhel Jaber

Sebastian Gracias

Muhammad M Khellah

Jonathan J Huang

Charles Augustine

Willem M Beltman

Joachim Hofer

Georg Stemmer

Josef G Bauer

Somnath Paul

Turbo Majumder

Piotr Rozen

Suyoung Bang

Tomasz Dorau

Jacek Ossowski

Maciej Muchlinski

Wootaek Lim

Sebastian Czyryba

Techniques for passive enrollment of a user in a speaker identification (ID) device are provided. One technique includes: parsing, by a processor of the speaker ID device, a speech sample, spoken by the user, into a keyword phrase sample and a command phrase sample; identifying, by a text-dependent speaker ID circuit of the speaker ID device, the user as the speaker of the keyword phrase sample; associating the command phrase sample with the identified user; determining if the command phrase sample in conjunction with one or more earlier command phrase samples associated with the user is sufficient command phrase sampling to enroll the user in a text-independent speaker ID circuit of the speaker ID device; and enrolling the user in the text-independent speaker ID circuit using the command phrase samples associated with the user after determining there is sufficient command phrase sampling to enroll the user.

Passive enrollment method for speaker identification systems

A system, article, and method provide temporal-domain feature extraction for automatic speech recognition.

Method and system of temporal-domain feature extraction for automatic speech recognition

A method and system are directed to autonomous neural network keyphrase detection and includes generating and using a multiple element state score vector by using neural network operations and without substantial use of a digital signal processor (DSP) to perform the keyphrase detection.

Method and system of neural network keyphrase detection

An example apparatus for generating dialogue includes an audio receiver to receive audio data including speech. The apparatus also includes a verification score generator to generate a verification score based on the audio data. The apparatus further includes a user detector to detect that the verification score exceeds a lower threshold but does not exceed a higher threshold. The apparatus includes a dialogue generator to generate dialogue to solicit additional audio data to be used to generate an updated verification score in response to detecting that the verification score exceeds a lower threshold but does not exceed a higher threshold.

Generating dialogue based on verification scores

Systems, apparatuses and methods for secure audio acquisition. The method includes receiving audio data via a digital microphone. The digital microphone outputs a single bit at a high sampling rate. The digital microphone output is converted to a full range audio signal. The full range audio signal is filtered to provide a band limited audio output that avoids capture of enough of a spectral range of speech for the speech to be intelligible.

Secure audio acquisition system with limited frequency range for privacy

Systems, apparatuses and methods for technology to perform gait detection and identification. The system includes a pre-processing pipeline to process audio input data from one or more microphones to combine and strengthen an audio gait signal. The pre-processing pipeline is coupled to a gait detector to detect the sound of one or more footsteps from the audio gait signal. The system also includes a person evaluator (e.g., identifier/verifier) to identify the person associated with the one or more footsteps using a set of trained footstep identification (ID) classifiers. Each trained footstep ID classifier is mapped to the gait of a specific person in the home based on a particular combination of person, footwear, and floor surface within the home.

Audio gait detection and identification

Technologies for identifying sounds are disclosed. A sound identification device may capture sound data, and split the sound data into frames. The sound identification device may then determine an acoustic feature vector for each frame, and determine parameters based on how each acoustic feature varies over the duration of time corresponding to the frames. The sound identification device may then determine if the sound matches a pre-defined sound based on the parameters. In one embodiment, the sound identification device may be a baby monitor, and the pre-defined sound may be a baby crying.

Technologies for robust crying detection using temporal characteristics of acoustic features

A plurality of modems or modem types can run on a host processor, a digital signal processor or both, either concurrently or selectively. Modules of more than one modem program can be swapped in and out of DSP memory space. Common modem code can be run on either a host processor or on a DSP using respective command libraries.

Multi-modem implementation with host based and digital signal processor based modems

System for dedicating a host processor to running one of a plurality of modem programs and dedicating a DSP to running another one of the modem programs

Growing community of inventors

El Dorado Hills, CA, United States of America

David Pearce