Merge pull request #1928 from pareenaverma/content_review

First tech review on voice assistant LP

Author: pareenaverma

content/learning-paths/mobile-graphics-and-gaming/voice-assistant/1-prerequisites.md

@@ -1,16 +1,16 @@
 ---
-title: Prerequisites
+title: Development environment
 weight: 3
 
 ### FIXED, DO NOT MODIFY
 layout: learningpathall
 ---
 
-## Install software required for this Learning Path
+## Install dependencies
 
-In this learning path, you will compile an Android application, so you first need to download and install the latest version of [Android Studio](https://developer.android.com/studio) on your computer.
+In this learning path, you will compile an Android application, so you first need to download and install the latest version of [Android Studio](https://developer.android.com/studio) on your development machine.
 
-You then need to ensure you have the following tools:
+You then need to install the following tools:
 - `cmake`, the software build system
 - `git`, the version control system for cloning the Voice Assistant codebase
 - `adb`, the Android Debug Bridge, a command-line tool to communicate with a device and perform various commands on it
@@ -19,9 +19,10 @@ These tools can be installed by running the following command (depending on your
 
 {{< tabpane code=true >}}
   {{< tab header="Linux/Ubuntu" language="bash">}}
-sudo apt install git adb cmake
+sudo apt update
+sudo apt install git adb cmake -y
   {{< /tab >}}
   {{< tab header="macOS" language="bash">}}
 brew install git android-platform-tools cmake
   {{< /tab >}}
-{{< /tabpane >}}
+{{< /tabpane >}}

content/learning-paths/mobile-graphics-and-gaming/voice-assistant/2-overview.md

@@ -6,25 +6,25 @@ weight: 4
 layout: learningpathall
 ---
 
-The Voice Assistant is an example application that demonstrates a complete voice interaction pipeline for Android.
+The Voice Assistant application demonstrates an example of a complete voice interaction pipeline for Android.
 
 It generates intelligent responses by utilizing:
-1. Speech-to-Text (STT) to transform the user's audio prompt into a text representation,
-2. a Large Language Model (LLM) to answer the user's prompt in text form,
-3. the Android Text-to-Speech (TTS) API is then used to produce a voice response.
+1. Speech-to-Text (STT) to transform the user's audio prompt into a text representation
+2. A Large Language Model (LLM) to respond to the user's prompt in text form
+3. Android Text-to-Speech (TTS) API to produce a voice response.
 
 ![example image alt-text#center](overview.png "Figure 1: Overview")
 
-These three steps correspond to specific components used in the Voice Assistant application. A more detailed description of each one follows.
+These three steps correspond to specific components used in the Voice Assistant application. A more detailed description of each step is provided.
 
 ## Speech to Text Library
 
 Speech-to-Text is also known as Automatic Speech Recognition. This part of the pipeline focuses on converting spoken language into written text.
 
 Speech recognition is done in the following stages:
-- The device's microphone captures spoken language as an audio waveform,
-- The audio waveform is broken into small time frames, and features are extracted to represent sound,
-- A neural network is used to predict the most likely transcription of audio based on grammar and context,
+- The device's microphone captures spoken language as an audio waveform.
+- The audio waveform is broken into small time frames, and features are extracted to represent sound.
+- A neural network is used to predict the most likely transcription of audio based on grammar and context.
 - The final recognized text is generated for the next stage of the pipeline.
 
 ## Large Language Models Library
@@ -35,6 +35,6 @@ The text transcription from the previous part of the pipeline is used as input t
 
 ## Text to Speech Component
 
-Currently, this part of the application pipeline uses the Android Text-to-Speech API with some extra functionality to ensure smooth and natural speech output.
+This part of the application pipeline uses the Android Text-to-Speech API with some extra functionality to ensure smooth and natural speech output.
 
-In synchronous mode, speech is only generated after the full response from the LLM is received. By default, the application operates in asynchronous mode, where speech synthesis starts as soon as a sufficient portion of the response (such as a half or full sentence) is available. Any additional responses are queued for processing by the Android Text-to-Speech engine.
+In synchronous mode, speech is only generated after the full response from the LLM is received. By default, the application operates in asynchronous mode, where speech synthesis starts as soon as a sufficient portion of the response (such as a half or full sentence) is available. Any additional responses are queued for processing by the Android Text-to-Speech engine.

content/learning-paths/mobile-graphics-and-gaming/voice-assistant/3-build.md

@@ -6,24 +6,30 @@ weight: 5
 layout: learningpathall
 ---
 
+In this section you will build the Voice Assistant application to run on your Android phone.
+
 ## Download the Voice Assistant
 
-```BASH
+Start by cloning the repository with the complete example application code:
+
+```bash
 git clone https://git.gitlab.arm.com/kleidi/kleidi-examples/real-time-voice-assistant.git voice-assistant.git
 ```
 
 ## Build the Voice Assistant
 
-Open Android Studio and open the project that you just downloaded in the preceding step:
+Open Android Studio and open the project that you downloaded in the previous step:
 
 ![example image alt-text#center](open_project.png "Figure 2: Open the project in Android Studio.")
 
 Build the application with its default settings by clicking the little hammer
-"Make Module 'VoiceAssistant.app'" button in the upper right corner:
+"Make Module `VoiceAssistant.app`" button in the upper right corner:
 
 ![example image alt-text#center](build_project.png "Figure 3: Build the project.")
 
-Android Studio will start the build, which may take some time if it needs to
-download some dependencies of the Voice Assistant app:
+Android Studio will start the build. The build may take some time if it needs to
+download some dependencies for the Voice Assistant app that are not already installed:
+
+![example image alt-text#center](build_success.png "Figure 4: Successful build!")
 
-![example image alt-text#center](build_success.png "Figure 4: Successful build!")
+Now that you have successfully built the Android application, you will run it in the next step.

content/learning-paths/mobile-graphics-and-gaming/voice-assistant/4-run.md

@@ -7,7 +7,7 @@ weight: 6
 layout: learningpathall
 ---
 
-In the previous section, we built the Voice Assistant app. Now, we need to install it on the phone. The easiest way to do this is to put the Android phone in developer mode and use a USB cable to upload the application.
+In the previous section, you built the Voice Assistant application. Now, you will install this application on your Android phone. The easiest way to do this is to put your Android phone in developer mode and use a USB cable to upload the application.
 
 ## Switch your phone to developer mode
 
@@ -26,7 +26,7 @@ The Voice Assistant will welcome you with this screen:
 
 ![example image alt-text#center](voice_assistant_view1.png "Figure 6: Welcome Screen")
 
-You can now press the part at the bottom and make your request!
+You can now use the Press to Talk at the bottom and make your request!
 
 ## Voice Assistant Controls
 

content/learning-paths/mobile-graphics-and-gaming/voice-assistant/_index.md

@@ -1,29 +1,24 @@
 ---
 title: Accelerate a Voice Assistant with KleidiAI and SME2
 
+draft: true
+cascade:
+    draft: true
+
 minutes_to_complete: 30
 
-who_is_this_for: This Learning Path is an introductory topic on improving the performances of a voice assistant by using KleidiAI and SME2.
+who_is_this_for: This is an introductory topic for software developers interested in running a voice assistant with improved performance on their Android phones by using KleidiAI and SME2.
 
 learning_objectives:
-    - Compile an Android application
-    - Use KleidAI and SME2 to improve the performance of the voice assistant
+    - Learn how to compile a voice assistant Android application.
+    - Use KleidiAI and SME2 to improve the performance of the voice assistant.
 
 prerequisites:
-    - an Android phone
-    - Android Studio
-    - CMake
-    - adb
-    - git
+    - An Android phone with support for i8mm (tested on Google Pixel 8 Pro).
+    - A development machine with [Android Studio](https://developer.android.com/studio) installed.
 
 author: Arnaud de Grandmaison
 
-test_images:
-    - ubuntu:latest
-test_link: null
-test_maintenance: true
-
-### Tags
 skilllevels: Introductory
 subjects: Performance and Architecture
 armips: