diff --git a/README.md b/README.md
index ea39464..4a52ba1 100644
--- a/README.md
+++ b/README.md
@@ -22,16 +22,16 @@ GCP = Google Cloud Platform
 ## Backend services
 
 1. ImageUpload
-  - After getting the base64 image posted to the API Gateway endpoint, *ImageUpload* service saves it in S3 and creates an record in DynamoDB. It also sends a message to SQS requesting image resizing.
+  - After getting the base64 image posted to the API Gateway endpoint, *ImageUpload* service saves it in S3 and creates a record in DynamoDB. It also sends a message to SQS requesting image resizing.
 
 2. ImageResizer
   - After picking up the image resizing request message from SQS, this service gets the original image from S3 and resizes them, updating the database with resized image urls.
 
 3. Vision
-  - Whenever a new image is inserted in S3, the bucket is configured to trigger this service, which requests OCR results from Google Vision API, and sends translation & NLP-English (Natural Language Processing) requests to SQS.
+  - Whenever a new image is inserted into S3, the bucket is configured to trigger this service, which requests OCR results from Google Vision API, and sends translation & NLP-English (Natural Language Processing) requests to SQS.
 
 4. Translate
-  - After picking up the translate request message from SQS, this service requests Google Translate API with Enlighs OCR results, updating the database with the translation text. Then it sends a NLP-ZH-TW request to SQS.  
+  - After picking up the translate request message from SQS, this service requests Google Translate API with English OCR results, updating the database with the translation text. Then it sends a NLP-ZH-TW request to SQS.  
 
 5. NLP
   - After picking up the NLP request message from SQS, this service requests Google NLP API, updating the database with the entities list. These may be English or Zh-Tw entities depending upon request.
@@ -42,10 +42,10 @@ GCP = Google Cloud Platform
 - Sign up on both AWS and GCP
 - Get GCP credentials (a key json file) and project ID
 - Create your lambda functions, with the following caveat
-- Set the env variables relating to GCP for Vision, Translate, NLP services for your lambdas
-- Normally to deploy to a lambda function you `npm install`, `zip` everything and upload to the lambda function
-- However, for `ImageResizer`, `Vision` and `NLP` there's a build step after `npm install`, and it won't build correctly if you build locally on your Mac or Windows machines.
-- So, you need to either 1) build it inside a docker container with Amazon Machine Image (AMI) Linux or 2) build it on a AMI Linux EC2 instance. If this is too complex, ask this repo author (join@nltr.tw) for zipped `node_modules` files with the correct built files.
+  - Set the env variables relating to GCP for Vision, Translate, NLP services for your lambdas
+  - Normally to deploy to a lambda function you `npm install`, `zip` everything and upload to the lambda function
+  - However, for `ImageResizer`, `Vision` and `NLP` there's a build step after `npm install`, and it won't build correctly if you build locally on your Mac or Windows machines.
+  - So, you need to either 1) build it inside a docker container with Amazon Machine Image (AMI) Linux or 2) build it on a AMI Linux EC2 instance. If this is too complex, ask this repo author (join@nltr.tw) for zipped `node_modules` files with the correct built files.
 
 ## Future plans