11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

The QUT-NOISE-TIMIT Corpus for the Evaluation of Voice Activity Detection Algorithms

David Dean, Sridha Sridharan, Robert Vogt, Michael Mason

Queensland University of Technology, Australia

The QUT-NOISE-TIMIT corpus consists of 600 hours of noisy speech sequences designed to enable a thorough evaluation of voice activity detection (VAD) algorithms across a wide variety of common background noise scenarios. In order to construct the final mixed-speech database, a collection of over 10 hours of background noise was conducted across 10 unique locations covering 5 common noise scenarios, to create the QUT-NOISE corpus. This background noise corpus was then mixed with speech events chosen from the TIMIT clean speech corpus over a wide variety of noise lengths, signal-to-noise ratios (SNRs) and active speech proportions to form the mixed-speech QUT-NOISE-TIMIT corpus. The evaluation of five baseline VAD systems on the QUT-NOISE-TIMIT corpus is conducted to validate the corpus and show that the variety of noise available will allow for better evaluation of VAD systems than existing approaches in the literature.

Full Paper

Bibliographic reference.  Dean, David / Sridharan, Sridha / Vogt, Robert / Mason, Michael (2010): "The QUT-NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms", In INTERSPEECH-2010, 3110-3113.