Speakers and VCV material
Twelve female and 12 male native English talkers aged between 18-49 contributed to the corpus.
Speakers produced each of the 24 consonants (/b/, /d/, /g/, /p/, /t/, /k/, /s/, / See the Technical details page for further details of the collection and postprocessing procedure. Training, development and test setsTraining material comes from 8 male and 8 female speakers while tokens from the remaining 8 speakers are used in the independent test set. A development set will be released shortly. After removing unusable tokens identified during post-processing, the training set consists of 6664 clean tokens. Seven tests sets, corresponding to a quiet and 6 noise conditions, are available. Each test set contains 16 instances of each of the 24 consonants, for a total of 384 tokens. Listeners will identify consonants in each of the test conditions. Minimally, each contribution to the special session should report results on some or all of the test sets. Scoring software will be released in February 2008. NoiseThe table shows the 7 conditions:
These noise types provide a challenging and varied range of conditions. Signal-to-noise ratios were determined using pilot tests with listeners with the goal of producing similar identification scores (~ 65-70%) in each noise condition. VCV tokens are additively embedded in noise samples of duration 1.2s. The SNR is computed token-wise and refers to the SNR in the section where the speech and noise overlap. The time of onset of each VCV takes on one of 8 values ranging from 0 to 400 ms. In addition, test materials are also available as "stereo" sound files which are identical to the test sets except that the the noise and VCV tokens are in separate channels. We have made the test material available in this form to support computational models of human consonant perception which may wish to make some assumptions about e.g. ideal noise processing, and also to allow for the computation of idealised engineering systems (e.g. to determine performance ceilings). Of course, contributors should clearly distinguish which of their results are based on the single-channel and dual-channel noise sets. Download training, test, and development material. |