fix link to be relative
@@ -29,7 +29,7 @@ This section of documentation assumes the following:
Whilst Mycroft runs on a Raspberry Pi 3B or above, this is achieved through a custom release of Raspbian Lite significantly reducing the system overhead by not running a desktop environment and other unnecessary processes. Mycroft will run on older hardware however your experience may vary significantly.
-Our [Precise wake word engine](https://github.com/MycroftAI/mycroft-precise#mycroft-precise) also relies upon TensorFlow. For x86 Intel processors this requires the AVX \(Advanced Vector Extensions\) instruction set. To ensure your system supports AVX open a terminal and run: `grep avx /proc/cpuinfo`. AVX should be listed under the flags for each CPU core. If nothing is returned it is most likely that your system does not support AVX. Technical users may be able to build an older version of TensorFlow \(1.13\) from source using the [instructions provided on their website](https://www.tensorflow.org/install/source). Alternatively you may use Mycroft with the PocketSphinx wake word engine; see (Switching Wake Word Listeners)[https://mycroft-ai.gitbook.io/docs/using-mycroft-ai/customizations/wake-word#switching-wake-word-listeners].
+Our [Precise wake word engine](https://github.com/MycroftAI/mycroft-precise#mycroft-precise) also relies upon TensorFlow. For x86 Intel processors this requires the AVX \(Advanced Vector Extensions\) instruction set. To ensure your system supports AVX open a terminal and run: `grep avx /proc/cpuinfo`. AVX should be listed under the flags for each CPU core. If nothing is returned it is most likely that your system does not support AVX. Technical users may be able to build an older version of TensorFlow \(1.13\) from source using the [instructions provided on their website](https://www.tensorflow.org/install/source). Alternatively you may use Mycroft with the PocketSphinx wake word engine; see (Switching Wake Word Listeners)[../customizations/wake-word#switching-wake-word-listeners].
The ARM architecture has a similar requirement called SIMD \(Single Instruction, Multiple Data\). This has been available since ARMv7 which includes the Cortex A53 used by the RaspberryPi and the Cortex A7 from the OrangePi.
