I believe you can do what you want through standard Word Processing software by converting your data into a table or spreadsheet, using the word "Partner" to mark the entries. In particular, if you use a spreadsheet, you can sort the entries to separate the two partners, and then reimport each separate set of entries to a word processing program.

Looking at your example, an even simpler approach might be to use a word processor to to delete the paragraph markers after the ":" so that each person's text is in a paragraph that begins with either "Partner A:" or "Partner B:" and then sort those paragraphs.

Personally, I would do this sort of thing in Python 3, which is free, high-level, has a number of nice distributions with built-in IDEs, and is pretty quick to learn. I just spent a few minutes looking over your example, and I think I produced the behavior you desire with the following code:

infile = open('*the file path containing your source text*', 'r')

outfile_partner_a = open('*the path where you want partner a's output text*', 'w')

outfile_partner_b = open('the path where you want partner b's output text*', 'w')

current_outfile = outfile_partner_a

for aline in infile:

if aline == ('Partner A:' + '\n'):

current_outfile = outfile_partner_a

elif aline == ('Partner B:' + '\n'):

current_outfile = outfile_partner_b

else:

current_outfile.write(aline)

infile.close()

outfile_partner_a.close()

outfile_partner_b.close()

When this is executed, the output text file for Partner A is:

Hello how are you?

Im good, What year are you in?

And the output text file for Partner B is:

Hey, Im good thank hbu?

Im in forth year.

(As a note, after I posted this the first time RG dropped the tabbing. Python is sensitive to whitespace, so the formatting of the "for" loops and conditionals is not quite right in the example above. But a bit of study will show you where the tabs should be added.)

Peter A. Krause has given a great answer. I also believe I have accomplished the desired result using Python 3. I used regular expression to pattern matching which should also cover typos. In other words it will match the following (Partner A:, partner a:, Partner A, partnera, Partnera, etc.). In order to run the attached file (split_text.py), you will need save you Word document as .txt file. Open (split_text.py) and change "sample_text.txt" to the name of your file. Make sure that both the .py and .txt files are in the same folder.

I decided to test my suggestion and accomplished what you need quite easily using Microsoft Word. The only thing you need to know is that Word uses the character combination "^p" for paragraph breaks.

I did a cut and paste to put your sample text into Word, and the first command can be summarized as:

Replace All :^p with : (that is, "coloncaretp" with "colon" to cut out the paragraphs)

This produces:

Partner A:Hello how are you?

Partner B:Hey, Im good thank hbu?

Partner A:Im good, What year are you in?

Partner B:Im in forth year.

Next, select all the text and then go to the Tables menu. Choose "Sort" and the default is "paragraphs" to produce the following result:

Partner A:Hello how are you?

Partner A:Im good, What year are you in?

Partner B:Hey, Im good thank hbu?

Partner B:Im in forth year.

I suspect your actual data might be more complex than this sample, but there is a lot of other essentially hidden functionality in Word, so PM me and I might be able to help with that as well.