يفان زانغ | Hamad Bin Khalifa University

يفان زانغ

مهندس سوفت وير أول

البريد الإلكتروني

yzhang@hbku.edu.qa

الهاتف

+974 445 46129

موقع المكتب

مجمع البحوث بي1 - 1130

يفان زانغ

مهندس سوفت وير أول

المؤهلات العلمية

Master of Science (with Distinction)

Lion Labaroratories Prize for Best Project

الكيان

معهد قطر لبحوث الحوسبة

Divison

تقنيات اللغة العربية

السيرة الذاتية

Mr. Yifan have worked in industry for more than 10 years in researching and developing speech recognition and language related products. Prior joining QCRI, he was on the mission of building information discovery engine for innovative news services. He has been key member as a full stack research scientist in developing speech recognition engine serving millions of customers in  speech recognition teams of both SpinVox Nuance and Autonomy.

Master of Science (with Distinction)

Cardiff University, UK

2004

Lion Labaroratories Prize for Best Project

Cardiff University, Cardiff, UK

2001

  • Artificial Intelligence
  • Speech Recognition
  • Knowledge Graph

Senior Software Engineer

Qatar Computing Search Institute, Qatar

2013 ~

Sr. Research Engineer

Wavii (Google), US

2012 ~ 2013

Senior Research Engineer

SpinVox (Nuance), UK

2008 ~ 2012

R&D Engineer

Autonomy, UK

2005 ~ 2008

Lead Developer

Tianchuang Software, China

2001 ~ 2002

  • The MGB-2 Challenge: Arabic Multi-Dialect Broadcast Media Recognition. In Proceedings of the Spoken Language Technology Workshop (SLT 2016) IEEE, California, USA.
  • QAT2 – The QCRI Advanced Transcription and Translation System. In Proceedings of INTERSPEECH 2015. Dresden, Germany. September 2015.
  • A Complete Kaldi Recipe For Building Arabic Speech Recognition Systems. In Proceedings of the Spoken Language Technology Workshop (SLT 2014) IEEE, Nevada, USA, December 2014.
  • In Proceedings of the Spoken Language Technology Workshop (SLT 2014) IEEE, Nevada, USA, December 2014.
  • Recent Advances in ASR Applied to an Arabic Transcription System for Al-Jazeera. In Proceedings of the Conference INTERSPEECH, Singapore, September 2014.
  • The MGB-2 Challenge: Arabic Multi-Dialect Broadcast Media Recognition. In Proceedings of the Spoken Language Technology Workshop (SLT 2016) IEEE, California, USA.