Bureaucrats, dave_user, Administrators
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= History =
{| class="wikitable" border="1"
!VersionID#
!Date
!Notes
|-
|1.0.0{{oldid|16244| 16244}}|December 202128/02/2022
|First public release
|-
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! style="border-left:solid 2px #73B2C7; border-right:solid 2px #73B2C7;border-top:solid 2px #73B2C7; border-bottom:solid 2px #73B2C7; background-color:#ededed; padding:5px; color:#000000" |17/01/2023
! style="border-left:solid 2px #73B2C7; border-right:solid 2px #73B2C7;border-top:solid 2px #73B2C7; border-bottom:solid 2px #73B2C7; background-color:#ededed; padding:5px; color:#000000" |Update testbed information
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=Testbed=
The testbed is illustrated in the following picture. Basically, it consists of an [[ORCA_SBC|Orca Single Board Computer]] TBDwith an USB to Audio adapter for an easy audio playback: [[File:ORCA_SBC-USB-audio-adapter.png | 500px | thumb|center| ORCA SBC with the USB audio adapter]]
More information on how to connect and use the USB Audio adapter in the following [[DESK-MX8-AN-0002:_Adding_an_audio_interface_with_an_USB_bluetooth_audio_transmitter | Application Note]]
=Implementation=
== Additional notes regarding the inference application ==
IAPP runs the inference on a convolutional neural network (CNN) trained to spot a predefined set of keywords. The CNN was trained with TensorFlow on several audio spectrogramson the basis of [https://www.tensorflow.org/tutorials/audio/simple_audio this] tutorial. It was then deployed in TensorFlow Lite format.
Before running the inference, IAPP pre-processes the audio samples to match the format used to train the CNN.
=Testing=