diff --git a/README.md b/README.md
index e1cc26a..2f28b74 100644
--- a/README.md
+++ b/README.md
@@ -1,27 +1,30 @@
 # Overview
 - A speech recognizer built on Vosk that can be run on the browser, inspired by [vosk-browser](https://github.com/ccoreilly/vosk-browser), but built from scratch and no code taken!
 - Designed with basic/nothrow exception safety
-- See the *examples* folder for examples on using the API 
+- See the *examples* folder for examples on using the API.
 - See the *devel* folder for the newest build (not guaranteed to work) and the JS build script
 
-# Compared to vosk-browser:
+# Compared to vosk-browser
 - Support multiple models
-- Model storage path management
-- Model ID management (for model updates)
-- Smaller JS size (>3.1MB vs 1.4MB gzipped)
-- All related files (pthread worker, worklet processor,...) are merged
-- Shorter from-scratch build time
-- Faster loading and processing time
+- Has models' storage path management
+- Has models' ID management (for model updates)
+- Has smaller JS size (>3.1MB vs 1.4MB gzipped)
+- All related files (pthread worker, audio worklet processor,...) are merged
+- Has shorter from-scratch build time
+- Has faster startup time
 
 # Basic usage (microphone recognition)
+- Result are logged to the console.
 ```
 <!DOCTYPE html>
 <html>
   <head>
-    <script src="Vosklet.js" async defer></script>
+    <script src="https://cdn.jsdelivr.net/gh/msqr1/Vosklet@1.0.0/Vosklet.js" async defer></script>
     <script>
       async function start() {
+        // Make sure sample rate matches that in the training data
         let ctx = new AudioContext({sampleRate : 16000})
+        // Setup mic with correct sample rate
         let micNode = ctx.createMediaStreamSource(await navigator.mediaDevices.getUserMedia({
           video: false,
           audio: {
@@ -31,16 +34,20 @@
             sampleRate: 16000
           },
         }))
+        // Load Vosklet module, model and recognizer
         let module = await loadVosklet()
         let model = await module.createModel("en-model.tgz","model","ID")
         let recognizer = await module.createRecognizer(model, 16000)
+        // Listen for result and partial result
         recognizer.addEventListener("result", ev => {
           console.log("Result: ", ev.detail)
         })
         recognizer.addEventListener("partialResult", ev => {
           console.log("Partial result: ", ev.detail)
         })
+        // Create a transferer node to get audio data on the main thread
         let transferer = await module.createTransferer(ctx, 128 * 150)
+        // Recognize data on arrival
         transferer.port.onmessage = ev => {
           recognizer.acceptWaveform(ev.data)
         }
diff --git a/examples/fromMic.html b/examples/fromMic.html
index 8372a17..dee48be 100644
--- a/examples/fromMic.html
+++ b/examples/fromMic.html
@@ -4,7 +4,9 @@
     <script src="Vosklet.js" async defer></script>
     <script>
       async function start() {
+        // Make sure sample rate matches that in the training data
         let ctx = new AudioContext({sampleRate : 16000})
+        // Setup mic with correct sample rate
         let micNode = ctx.createMediaStreamSource(await navigator.mediaDevices.getUserMedia({
           video: false,
           audio: {
@@ -14,15 +16,18 @@
             sampleRate: 16000
           },
         }))
+        // Load Vosklet module, model and recognizer
         let module = await loadVosklet()
         let model = await module.createModel("en-model.tgz","model","ID")
         let recognizer = await module.createRecognizer(model, 16000)
+        // Listen for result and partial result
         recognizer.addEventListener("result", ev => {
           console.log("Result: ", ev.detail)
         })
         recognizer.addEventListener("partialResult", ev => {
           console.log("Partial result: ", ev.detail)
         })
+        // Create a transferer node to get audio data
         let transferer = await module.createTransferer(ctx, 128 * 150)
         transferer.port.onmessage = ev => {
           recognizer.acceptWaveform(ev.data)
diff --git a/examples/fromWav.html b/examples/fromWav.html
index 525b5a9..3e681af 100644
--- a/examples/fromWav.html
+++ b/examples/fromWav.html
@@ -4,6 +4,7 @@
     <script src="Vosklet.js" async defer></script>
     <script>
        async function start() {
+        // Make sure sample rate matches that in the training data
         let ctx = new AudioContext({sampleRate : 16000})
         let module = await loadVosklet()
         let model = await module.createModel("en-model.tgz","model","ID")
@@ -14,6 +15,7 @@
         recognizer.addEventListener("partialResult", ev => {
           console.log("Partial result: ", ev.detail)
         })
+        // Fetch, decode, and recognize .wav
         let wav = await fetch("example.wav")
         let audioBuf = await ctx.decodeAudioData(await wav.arrayBuffer())
         recognizer.acceptWaveform(audioBuf.getChannelData(0))
