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<p>Projectje: met voiceherkenning een transcriptie van het Journaal
maken, de zinnen vervolgens random verhaspelen en vervangen en mbv
AI Text-to speech een alternatief journaal maken... Met
teletekstnieuws is het wellicht makkelijker te implementeren. MMM,
als ik de tijd er voor vind is het misschien een artistieke poging
waard...</p>
<p>RO<br>
</p>
<p><br>
</p>
<p><font color="#26a269">import random<br>
import re<br>
<br>
def substitute_subject_object(sentence):<br>
subjects = ["I", "You", "He", "She", "They", "We", "The
cat", "The dog", "The bird", "The robot"]<br>
objects = ["apple", "book", "car", "dog", "house", "pen",
"table", "tree", "umbrella", "watch"]<br>
<br>
# Find the subject and object using regular expressions<br>
match = re.match(r'(.+?)(\b(?:loves|likes)\b)(.+)',
sentence)<br>
if not match:<br>
return sentence<br>
<br>
subject = match.group(1).strip()<br>
verb = match.group(2).strip()<br>
direct_object = match.group(3).strip()<br>
<br>
# Randomly substitute the subject and object<br>
new_subject = random.choice(subjects)<br>
new_object = random.choice(objects)<br>
<br>
# Build the new sentence<br>
new_sentence = f"{new_subject} {verb} {new_object}."<br>
return new_sentence<br>
<br>
# Example usage<br>
sentence = "She likes dogs."<br>
new_sentence = substitute_subject_object(sentence)<br>
print("Original sentence:", sentence)<br>
print("New sentence:", new_sentence)<br>
</font></p>
<p>--<br>
</p>
<p>Voorbeeld:</p>
<p><br>
</p>
<p>reinold@fedora test]$ python directobject2.py<br>
Original sentence: She likes dogs.<br>
New sentence: The robot likes umbrella.<br>
<br>
Original sentence: She likes dogs.<br>
New sentence: The robot likes pen.<br>
<br>
Original sentence: She likes dogs.<br>
New sentence: He likes tree.<br>
<br>
Original sentence: She likes dogs.<br>
New sentence: I likes book.<br>
<br>
Original sentence: She likes dogs.<br>
New sentence: The cat likes house.<br>
</p>
<p>--<br>
</p>
<p><br>
</p>
<p>RO: improve this program with a large set of words of verbs,
objects and subjects</p>
<p>ChatGPT: Certainly!</p>
<p><br>
</p>
<p><font color="#26a269">import random<br>
import re<br>
</font></p>
<font color="#26a269"><br>
def load_word_list(filename):<br>
with open(filename, 'r') as file:<br>
word_list = [word.strip() for word in file.readlines()]<br>
return word_list<br>
<br>
def substitute_subject_verb_object(sentence, subject_list,
verb_list, object_list):<br>
# Find the subject, verb, and object using regular expressions<br>
match = re.match(r'(.+?)\b(.*?)\b(.+)', sentence)<br>
if not match:<br>
return sentence<br>
<br>
subject = match.group(1).strip()<br>
verb = match.group(2).strip()<br>
direct_object = match.group(3).strip()<br>
<br>
# Randomly substitute the subject, verb, and object<br>
new_subject = random.choice(subject_list)<br>
new_verb = random.choice(verb_list)<br>
new_object = random.choice(object_list)<br>
<br>
# Build the new sentence<br>
new_sentence = f"{new_subject} {new_verb} {new_object}."<br>
return new_sentence<br>
<br>
# Load subject, verb, and object word lists<br>
subject_word_list = load_word_list('subject_words.txt')<br>
verb_word_list = load_word_list('verb_words.txt')<br>
object_word_list = load_word_list('object_words.txt')<br>
<br>
# Example usage<br>
sentence = "She likes dogs."<br>
new_sentence = substitute_subject_verb_object(sentence,
subject_word_list, verb_word_list, object_word_list)<br>
print("Original sentence:", sentence)<br>
print("New sentence:", new_sentence)<br>
</font><br>
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