Kenneth Booker - Detroit MI Mark R. Dunneback - Macomb Township MI Joseph Guerra - Sterling Heights MI Lianchun Mu - Novi MI Enoch Nartey - Troy MI
Assignee:
Chrysler Corporation - Auburn Hills MI
International Classification:
B23K 3112 B23K 2600 B21J 1308
US Classification:
228102
Abstract:
A workpiece is held at a welding station by several clamps during welding. After welding, the workpiece is transferred to a checking station where a determination is made of the actual location of critical points on the workpiece. The actual critical point locations are compared with ideal critical point locations to determine if there is any error in the manner in which the workpiece was held by the clamps. If an error is determined, one or more of the clamps are adjusted to compensate for the error when holding a subsequent workpiece for welding. Apparatus is also provided for carrying out the method of this invention.
Automated Deep Learning Based On Customer Driven Noise Diagnostic Assist
- Detroit MI, US Kenneth Ray Booker - Grosse Pointe Woods MI, US William L. Villaire - Clarkston MI, US Jeffery J. Milton - Clarkston MI, US Mathew Anthony Clifford Keith Jones - Oshawa, CA
Assignee:
GM GLOBAL TECHNOLOGY OPERATIONS LLC - Detroit MI
International Classification:
G07C 5/08 G06K 9/62
Abstract:
Methods and apparatus are provided for diagnosing a vehicle. In one embodiment, a method includes: initiating, by a processor, a recording of a noise by at least one microphone based on user selection data from a user of the vehicle; receiving, by the processor, audio signal data based on the recording; generating, by the processor, vector data based on the audio signal data; processing, by the processor, the vector data with at least one trained machine, by the processor, learning model to determine a classification of the noise; predicting, by the processor, an action to be taken based on the classification; and storing, by the processor, the audio signal data, the classification, and the action in a datastore.
Automated Speech Recognition Using A Dynamically Adjustable Listening Timeout
- Detroit MI, US Kenneth R. Booker - Grosse Pointe Woods MI, US
International Classification:
G10L 25/78 G10L 15/22
Abstract:
A system and method of automated speech recognition using a dynamically-adjustable listening timeout. The method includes: receiving speech signals representing a first speech segment during a first speech listening period; during the first speech listening period, processing the received speech signals representing the first speech segment to determine whether the first speech segment includes one or more insignificant utterances; adjusting a listening timeout in response to the determination of whether the first speech segment includes one or more insignificant utterances; listening for subsequent received speech using the adjusted listening timeout; and performing automatic speech recognition on the received speech signals and/or the subsequently received speech signals.
- Detroit MI, US Xu Fang Zhao - Lasalle, CA Scott M. Pennock - Lake Orion MI, US Kenneth R. Booker - Grosse Pointe Woods MI, US
International Classification:
G10L 15/22 G06F 3/0482 G10L 15/18 G10L 15/30
Abstract:
A method and associated system for recognizing speech using multiple speech recognition algorithms. The method includes receiving speech at a microphone installed in a vehicle, and determining results for the speech using a first algorithm, e.g., embedded locally at the vehicle. Speech results may also be received at the vehicle for the speech determined using a second algorithm, e.g., as determined by a remote facility. The results for both may include a determined speech topic and a determined speech slotted value, along with corresponding confidence levels for each. The method may further include using at least one of the determined first speech topic and the received second speech topic to determine the topic associated with the received speech, even when the first speech topic confidence level of the first speech topic, and the second speech topic confidence level of the second speech topic are both a low confidence level.
Persistent Training And Pronunciation Improvements Through Radio Broadcast
- Detroit MI, US Kenneth R. BOOKER - Detroit MI, US Xu Fang ZHAO - LaSalle, CA
International Classification:
G10L 15/22 G10L 15/26 B60R 16/037
Abstract:
A processor receives a broadcast in a vehicle, select audio data from the broadcast, processes the audio data selected from the broadcast, determines a phonetic pattern of the selected audio data based on the processing, selects additional instances of audio data from the broadcast that resemble the selected audio data, processes the additional instances of audio data from the broadcast, determine phonetic patterns of the additional instances of audio data, and selects a plurality of phonetic patterns from the phonetic pattern of the selected audio data and the phonetic patterns of the additional instances of audio data. A transmitter transmits the plurality of phonetic patterns to a server to determine an optimal pronunciation of the selected audio data based on a statistical analysis of the plurality of phonetic patterns and to add the optimal pronunciation of the selected audio data to a database used to recognize speech in the vehicle.
Name / Title
Company / Classification
Phones & Addresses
Kenneth Booker
Dish Network Cable Tv Service · Satellite Tv Service
122 1 St, Elizabeth, NJ 07201 (908)6362045
Resumes
Bluetooth Design And Release Engineer At Nissan Technical Center North America
Design Release Engineer - Bluetooth Systems at Nissan Technical Center North America
Location:
Greater Detroit Area
Industry:
Automotive
Work:
Nissan Technical Center North America - Farmington Hills, MI since Oct 2012
Design Release Engineer - Bluetooth Systems
General Motors - Warren, MI Jul 2011 - Oct 2012
Electrical Diagnostic Development Engineer
General Motors - Warren, MI Jun 2008 - Jul 2011
Electrical Service Parts Engineer
General Motors - Warren, MI May 2007 - Aug 2007
Service Information Development Intern
General Motors - Romulus, MI May 2006 - Aug 2006
Tech 2 & Next-Gen Hardware Development Intern
Education:
Michigan State University 2004 - 2008
Bachelors of Science, Electrical Engineering
Skills:
Electrical Engineering Critical Thinking Circuit Analysis Teamwork Troubleshooting Hardware Unified Communications Quality Assurance Creative Problem Solving Product Validation Cross-functional Coordination Analytical Approach Seeing The Big Picture