[Univ of Cambridge] [Dept of Engineering]


[ Description | Personnel | Partners | Publications ]

Project Description

"The Babel Program will develop agile and robust speech recognition technology that can be rapidly applied to any human language in order to provide effective search capability for analysts to efficiently process massive amounts of real-world recorded speech. Today's transcription systems are built on technology that was originally developed for English, with markedly lower performance on non-English languages. These systems have often taken years to develop and cover only a small subset of the languages of the world. Babel intends to demonstrate the ability to generate a speech transcription system for any new language within one week to support keyword search performance for effective triage of massive amounts of speech recorded in challenging real-world situations."

To achieve these aims, the CUED Speech Group within the Lorelei team will examine and develop:

  • state-of-the-art speech recognition systems and integration with keyword spotting;
  • multi-lingual and language-independent speech recognition systems;
  • model-based approaches to noise and channel distortions.

Personnel Associated with the Project

Former members:

  • Simon Au [Fourth Year Undergraduate]
  • Martin Blake [UROP Student]
  • Leo Chen [Fourth Year Undergraduate]
  • Ed Dakin [Fourth Year Undergraduate]
  • Jiameng Gao [Fourth Year Undergraduate (and former UROP Student)]
  • Siddhant Jayakumar [UROP Student]
  • Andrey Malinin [Fourth Year Undergraduate]
  • Sean Quah [Fourth Year Undergraduate]
  • Dr Shakti Rath [Research Associate]
  • Alex Riley [UROP Student]
  • Danielle Saunders [Fourth Year Undergraduate]
  • Dr Haipeng Wang [Research Associate]
  • Justin Yang [Research Student (part funded)]
  • Dr Austin Zhang [Research Student (part funded)]
  • Chao Zhang [Research Student (part funded)]

Lorelei Consortium Partners



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