diff --git a/project-preplanning.org b/project-preplanning.org
index 1b9e967..0c94fb2 100644
--- a/project-preplanning.org
+++ b/project-preplanning.org
@@ -20,7 +20,7 @@ While apps exist for the two questionnaires mentioned in the `pitch', there is s
  - combined app :: most simply, there are two apps, having a single app for both questionnaires is surely preferable (/stretch goal/: define questionnaires in eg JSON, the app can dynamically expand without needing updated)
  - encryption :: even though the data is stored locally, it is still worthwhile to encrypt it at rest for privacy reasons
  - export‡ :: being able to export eg a PDF or similar would be a boon for sharing with clinicians (eg this could be printed off to be added to notes); other formats are possible too
- - patient notes† :: being able to take freetext notes, which could be associated with a questionnaire or be `freestanding', would aid memory for patients in consulations
+ - patient notes† :: being able to take free text notes, which could be associated with a questionnaire or be `freestanding', would aid memory for patients in consultations
  - graphing† :: since these questionnaires usually produce a score, this could be charted over time (handy for spotting patterns)
  - reminders† :: a periodic notification (eg weekly, bi-weekly, monthly) would help remind patients to track their symptoms
 
@@ -50,7 +50,7 @@ Where the video is quiet it is unlikely to be a highlight. Interesting bits migh
 
  1. where the *audio level peaks* (eg someone speaking under stress, multiple people speaking, loud part of a game)
  2. where there is *laughter*, something funny probably happened or was said
- 3. where there is lots of *motion* something interesting may be happening:w
+ 3. where there is lots of *motion* something interesting may be happening
 
 To find these points:
 
@@ -72,7 +72,7 @@ There are a few caveats:
 
  - I don't know how well the `laughter detection' model works with the sample data (ie my own video files)
  - I don't know the first thing about training a model or tuning one (I suspect I would need several thousands of samples to train, perhaps fewer to tune?)
- - I lack hardware for tuning (my GPU is ancient and doesn't have features of newer GPUS)
+ - I lack hardware for tuning (my GPU is ancient and doesn't have features of newer GPUs)
  - Working with video files can be quite slow in general
 
 ** How This Project Might Proceed