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authorRichard Burton <richard.burton@arm.com>2021-11-10 16:27:14 +0000
committerRichard <richard.burton@arm.com>2021-11-10 16:34:16 +0000
commit005534664e192cf909a11435c4bc4696b1f4c51f (patch)
treef8314bd284561e1f0ff68fc393ee22d0318ae162 /docs/sections/arm_virtual_hardware.md
parentdee53bc7769d6201ec27deea4405c0df6c9b0623 (diff)
downloadml-embedded-evaluation-kit-005534664e192cf909a11435c4bc4696b1f4c51f.tar.gz
MLECO-2354 MLECO-2355 MLECO-2356: Moving noise reduction to public repository
* Use RNNoise model from PMZ * Add Noise reduction use-case Signed-off-by: Richard burton <richard.burton@arm.com> Change-Id: Ia8cc7ef102e22a5ff8bfbd3833594a4905a66057
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@@ -23,5 +23,5 @@ Note that you can register to receive free AWS credits to use Arm Virtual Hardwa
You can find more information about Arm Virtual Hardware [here](https://arm-software.github.io/VHT/main/overview/html/index.html).
-Once you have access to the AWS instance, we recommend starting from the [quick start guide](../quick_start.md) in order to get familiar
+Once you have access to the AWS instance, we recommend starting from the [quick start guide](../quick_start.md#Quick-start-example-ML-application) in order to get familiar
with the ml-embedded-evaluation-kit. Note that on the AWS instance, the FVP is available under `/opt/FVP_Corstone_SSE-300`.