Jens S Olson

US Patent:

20130159371, Jun 20, 2013

Filed:

Jun 6, 2012

Appl. No.:

13/490129

Inventors:

Richard Fastow - Cupertino CA, US
Jens Olson - Saratoga CA, US
Ben Michael Shoham - Ramat Hasharon, IL

Assignee:

Spansion LLC - Sunnyvale CA

International Classification:

G06F 17/10

US Classification:

708490

Abstract:

Embodiments of the present invention include an apparatus, method, and system for acoustic modeling. In an embodiment, an arithmetic logic unit for computing a one-dimensional score between a feature vector and a Gaussian probability distribution vector is provided. The arithmetic logic unit includes a computational logic unit configured to compute a first value based on a mean value and a variance value associated with a dimension of the Gaussian probability distribution vector and a dimension of a feature vector, a look up table module configured to output a second value based on the variance value, and a combination module configured to combine the first value and the second value to generate the one-dimensional score.

US Patent:

20130339028, Dec 19, 2013

Filed:

Jun 15, 2012

Appl. No.:

13/524584

Inventors:

Stephan ROSNER - Campbell CA, US
Chen Liu - Woodridge IL, US
Jens Olson - Saratoga CA, US

Assignee:

Spansion LLC - Sunnyvale CA

International Classification:

G10L 11/00
G10L 15/00

US Classification:

704275, 704E11001

Abstract:

A voice activation system is provided. The voice activation system includes a first stage configured to output a first activation signal if at least one energy characteristic of a received audio signal satisfies at least one threshold and a second stage configured to transition from a first state to a second state in response to the first activation signal and, when in the second state, to output a second activation signal if at least a portion of a profile of the audio signal substantially matches at least one predetermined profile.

US Patent:

20130158996, Jun 20, 2013

Filed:

Jun 6, 2012

Appl. No.:

13/489799

Inventors:

Richard Fastow - Cupertino CA, US
Jens Olson - Saratoga CA, US

Assignee:

Spansion LLC - Sunnyvale CA

International Classification:

G10L 15/00

US Classification:

704240, 704E15001

Abstract:

Embodiments of the present invention include an apparatus, method, and system for acoustic modeling. The apparatus can include a senone scoring unit (SSU) control module, a distance calculator, and an addition module. The SSU control module can be configured to receive a feature vector. The distance calculator can be configured to receive a plurality of Gaussian probability distributions via a data bus having a width of at least one Gaussian probability distribution and the feature vector from the SSU control module. The distance calculator can include a plurality of arithmetic logic units to calculate a plurality of dimension distance scores and an accumulator to sum the dimension distance scores to generate a Gaussian distance score. Further, the addition module is configured to sum a plurality of Gaussian distance scores to generate a senone score.

US Patent:

20210027148, Jan 28, 2021

Filed:

Jul 22, 2019

Appl. No.:

16/518444

Inventors:

- Cambridge, GB
Jens OLSON - San Jose CA, US
Jared Corey SMOLENS - Santa Clara CA, US
Eric KUNZE - Santa Clara CA, US
Ian Rudolf BRATT - Portola Valley CA, US

International Classification:

G06N 3/063
H03M 7/30

Abstract:

A processor arranged to compress neural network activation data comprising an input module for obtaining neural network activation data. The processor also comprises a block creation module arranged to split the neural network activation data into a plurality of blocks; and a metadata generation module for generating metadata associated with at least one of the plurality of blocks. Based on the metadata generated a selection module selects a compression scheme for each of the plurality of blocks, and a compression module for applying the selected compression scheme to the corresponding block to produce compressed neural network activation data. An output module is also provided for outputting the compressed neural network activation data.

US Patent:

20150106405, Apr 16, 2015

Filed:

Oct 16, 2013

Appl. No.:

14/054884

Inventors:

- Sunnyvale CA, US
Richard Fastow - Cupertino CA, US
Jens Olson - Saratoga CA, US
Kenichi Kumatani - Sunnyvale CA, US

Assignee:

Spansion LLC - Sunnyvale CA

International Classification:

G06F 17/30

US Classification:

707795

Abstract:

A method, apparatus, and tangible computer readable medium for processing a Hidden Markov Model (HMM) structure are disclosed herein. For example, the method includes receiving Hidden Markov Model (HMM) information from an external system. The method also includes processing back pointer data and first HMM states scores for one or more NULL states in the HMM information. Second HMM state scores are processed for one or more non-NULL states in the HMM information based on at least one predecessor state. Further, the method includes transferring the second HMM state scores to the external system.

US Patent:

20140180694, Jun 26, 2014

Filed:

Dec 21, 2012

Appl. No.:

13/725260

Inventors:

- Sunnyvale CA, US
Ojas A. Bapat - Sunnyvale CA, US
Jens Olson - Saratoga CA, US

Assignee:

Spansion LLC - Sunnyvale CA

International Classification:

G10L 15/02

US Classification:

7042561

Abstract:

Embodiments of the present invention include an acoustic processing device and a method for traversing a Hidden Markov Model (HMM). The acoustic processing device can include a senone scoring unit (SSU), a memory device, a HMM module, and an interface module. The SSU is configured to receive feature vectors from an external computing device and to calculate senones. The memory device is configured to store the senone scores and HMM information, where the HMM information includes HMM IDs and HMM state scores. The HMM module is configured to traverse the HMM based on the senone scores and the HMM information. Further, the interface module is configured to transfer one or more HMM scoring requests from the external computing device to the HMM module and to transfer the HMM state scores to the external computing device.