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The workshop is for developers to share their experiences with Speech Activity Detection (SAD), Automated Speech Recognition(ASR), and Keyword Search (KWS) algorithms or systems when applied to the data sets included in the OpenSAT19 Evaluation. Data sets in the OpenSAT19 Evaluation included a Simulated Public Safety Communications data set, the Low Resource Language (LRL) Pashto from the Babel data set, and audio extracted from amateur online video from the Video Annotation for Speech Technologies (VAST) data set. Challenges for speech analytic systems from these data sets included: varying first responder types of environmental sounds, effects on speech from background noises (e.g., Lombard effect), foreign language, audio compression, and diverse recording equipment.
The table below shows the speech analytic tasks that were possible for each data domain in the Evaluation.
|
Domain |
Tasks |
Language |
|
Public Safety Communications |
SAD, ASR, KWS |
English |
|
Low Resource Language (LRL) |
SAD, ASR, KWS |
Pashto |
|
Audio from amateur online Videos (AfV) |
SAD, KWS |
English |
The OpenSAT19 Evaluation workshop provides an opportunity for teams that participated in the Evaluation to present and openly discuss details of their system and related research with other OpenSAT19 Evaluation participants and with the Evaluation coordinators. Since OpenSAT will continued as an annual event, developers will have an opportunity to discuss their experiences with the OpenSAT19 Evaluation process and provide suggestions for improvement.
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