Next Event

Date: March 23rd, 2017
“Deep Learning in Siri” by Dr. Alex Acero, Apple

Register

    

Want to volunteer?

The IEEE SCV CAS chapter is seeking volunteers to help with the organization of technical meetings. Please contact us.

    

SCV-CAS Mailing List

To subscribe or unsubcribe, please visit the IEEE SCV-CAS list.

Upcoming Events

The following schedule and location hold for most events, unless otherwise noted:

  • 6:30pm: Networking/Light Dinner
  • 7:00pm: Announcement
  • 7:05pm: Presentation
  • 8:15pm: Adjourn

Cost: Free. Food donation accepted: $2 for IEEE member, $5 for non-IEEE member.

Location: QualComm Santa Clara, Building B, 3165 Kifer Road, Santa Clara, CA

We would appreciate suggestions for speakers to present at our meetings in the future.

“Deep Learning in Siri” by Dr. Alex Acero, Apple

Date: March 23rd, 2017

IEEE Santa Clara Valley Circuits and Systems Society proudly co-sponsors the upcoming seminar of the Signal Processing chapter on Thursday, March 23, 2017 by Dr. Alex Acero, Apple with the title:

“Deep Learning in Siri”

Location:

AMD Commons Auditorium, 991 Stewart Dr., Sunnyvale, CA (map or Google Maps)

 

Need visitor registration to enter this facility. Please register here.

 

Schedule:

6:30pm: Check-in/Networking

7:00pm: Announcements

7:05pm: Presentation

8:15pm: Adjourn

 

Cost:

FREE for IEEE members

$5 for Others

Abstract:

Siri, Apple’s personal assistant, first shipped in 2011 as part of iOS and brought conversational agents into the mainstream. Users can access Siri from their iPhone, iPad, Apple Watch, AppleTV and Carplay in 21 languages. Deep learning has revolutionized the field of machine learning, making a big impact in both core algorithms and application areas like speech recognition, critical for Siri. Mixture Density Networks, a particular type of deep learning, now power Apple’s TTS engine, making Siri’s voices more natural, smoother, and allowing Siri’s personality to shine through. Accented speech, always a challenge for speech recognition systems, can be addressed by training deep neural networks and convolutional neural networks with various sources of data properly weighted in order to achieve a robust acoustic model.

 

Biography:

Alex Acero leads the speech team in Siri, Apple’s personal assistant for iPhone, iPad, Apple Watch, Apple TV, and Carplay. Before joining Apple in 2013, he spent twenty years with Microsoft Research, managing teams in Speech, Natural Language Processing, Information Retrieval, Multimedia, Communication and Computer Vision. His team at Microsoft Research built Bing Translator, and contributed to Xbox Kinect. From 1991-1993 he managed the speech team for Spain’s Telefonica. He has been granted 154 US patents.

Dr. Acero is IEEE Fellow and ISCA Fellow. He received the 2012 IEEE Signal Processing Society Best Paper Award for the paper “Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition” for pioneering the use of deep learning in large vocabulary speech recognition. Alex is co-author of the textbook “Spoken Language Processing” and over 250 technical papers, with an h-index of 61 according to Google Scholar. Dr. Acero is Affiliate Faculty at the University of Washington. Alex received an engineering degree from the Polytechnic University of Madrid, a Masters from Rice University, and a PhD from Carnegie Mellon.

Dr. Acero is a member of IEEE Board of Directors. He has served in many roles within the IEEE Signal Processing Society, including President, Director Industrial Relations, Vice President Technical Directions, Member-at-Large of the Board of Governors, Chair of the Speech Technical Committee, Associate Editor for IEEE Transactions Speech and Audio Processing and IEEE Signal Processing Letters, member of the Editorial Board of IEEE Signal Processing Magazine and IEEE Journal on Selected Topics in Signal Processing, Publications Chair for ICASSP98.

Registration link for this event is https://www.eventbrite.com/e/deep-learning-in-siri-tickets-32225767137



Recent Events


  • March 2017
    M T W T F S S
    « Nov    
     12345
    6789101112
    13141516171819
    20212223242526
    2728293031