[Comp-neuro] The KARA ONE Database: Phonological Categories in imagined and articulated speech

frank frank at cs.toronto.edu
Mon Aug 3 15:31:50 CEST 2015


 

We are making 24 GB of a new dataset, called Kara One, freely available.
This database combines 3 modalities (EEG, face tracking, and audio)
during imagined and articulated speech using phonologically-relevant
phonemic and single-word prompts. It is the result of a collaboration
between the Toronto Rehabilitation Institute (in the University Health
Network) and the Department of Computer Science at the University of
Toronto. 

In the associated paper (abstract below), we show how to accurately
classify imagined phonological categories solely from EEG data.
Specifically, we obtain up to 90% accuracy in classifying imagined
consonants from imagined vowels and up to 95% accuracy in classifying
stimulus from active imagination states using advanced deep-belief
networks. 

Data from 14 participants are available here:
http://www.cs.toronto.edu/~complingweb/data/karaOne/karaOne.html [1]. 

If you have any questions, please contact Frank Rudzicz at
frank at cs.toronto.edu. 

Best regards, 

Frank 

PAPER Shunan Zhao and Frank Rudzicz (2015) Classifying phonological
categories in imagined and articulated speech. _In Proceedings of ICASSP
2015_, Brisbane Australia 

ABSTRACT This paper presents a new dataset combining 3 modalities (EEG,
facial, and audio) during imagined and vocalized phonemic and
single-word prompts. We pre-process the EEG data, compute features for
all 3 modalities, and perform binary classification of phonological
categories using a combination of these modalities. For example, a
deep-belief network obtains accuracies over 90% on identifying
consonants, which is significantly more accurate than two baseline
support vector machines. We also classify between the different states
(resting, stimuli, active thinking) of the recording, achieving
accuracies of 95%. These data may be used to learn multimodal
relationships, and to develop silent-speech and brain-computer
interfaces. 
 

Links:
------
[1] http://www.cs.toronto.edu/~complingweb/data/karaOne/karaOne.html
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