originalmk/songs-lyrics-generator
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Added rhymes in lyrics generation.

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This commit is contained in:
Sebastian Kutny 2023-03-28 17:25:17 +02:00
parent 2a538004b3
commit 307c291862
2 changed files with 30 additions and 8 deletions
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8
main.py
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@ -26,13 +26,15 @@ def generate_song(name):
n_gram = int(input("Select number of words in Markov state: ")) n_gram = int(input("Select number of words in Markov state: "))
number_of_verses = int(input("Select number of verses: ")) number_of_verses = int(input("Select number of verses: "))
words_in_verses = int((int(input("Select number of words in verses: ")) - 1) / n_gram) words_in_verses = int((int(input("Select number of words in verses: ")) - 1) / n_gram)
degree_of_chain = int(input("Select degree of chain: ")) # degree_of_chain = int(input("Select degree of chain: "))
model = create_markov_model(dataset, n_gram, degree_of_chain) model = create_markov_model(dataset, n_gram)
print('\n') print('\n')
last_state = random.choice(list(model.keys())) last_state = random.choice(list(model.keys()))
rime = None
for i in range(number_of_verses): for i in range(number_of_verses):
generated_lyrics, last_state = generate_lyrics(model, last_state, words_in_verses) generated_lyrics, last_state = generate_lyrics(model, last_state, words_in_verses, True if i == 0 else False, rime)
print(generated_lyrics) print(generated_lyrics)
rime = last_state
last_state = random.choices(list(model[last_state].keys()), last_state = random.choices(list(model[last_state].keys()),
list(model[last_state].values()))[0] list(model[last_state].values()))[0]

30
markov_model.py
View File

@ -1,5 +1,6 @@
import random import random
import re import re
from nltk import SyllableTokenizer
from nltk.tokenize import word_tokenize from nltk.tokenize import word_tokenize
import pandas as pd import pandas as pd
import numpy as np import numpy as np
@ -29,7 +30,7 @@ def clean_data(name):
return dataset return dataset
def create_markov_model(dataset, n_gram, n_step): def create_markov_model(dataset, n_gram):
markov_model = {} markov_model = {}
for i in range(len(dataset) - 1 - 2 * n_gram): for i in range(len(dataset) - 1 - 2 * n_gram):
current_state, next_state = "", "" current_state, next_state = "", ""
@ -73,16 +74,35 @@ def create_markov_model(dataset, n_gram, n_step):
return markov_model return markov_model
def generate_lyrics(markov_model, start, limit): def generate_lyrics(markov_model, start, limit, isStartingVerse, rime):
n = 0 n = 0
current_state = start current_state = start
lyrics = "" lyrics = ""
lyrics += current_state + " " lyrics += current_state + " "
lyrics = lyrics[0].upper() + lyrics[1:] lyrics = lyrics[0].upper() + lyrics[1:]
while n < limit: while n < limit:
next_state = random.choices(list(markov_model[current_state].keys()), if n == limit - 1 and not isStartingVerse:
list(markov_model[current_state].values())) rime = rime.split(" ")[-1]
current_state = next_state[0] tk = SyllableTokenizer()
rime_syllab = tk.tokenize(rime)[-1]
rime_states = {}
for state, probability in markov_model[current_state].items():
word = state.split(" ")[-1]
syllab = tk.tokenize(word)[-1]
if rime_syllab == syllab and rime != word:
rime_states.update({state: probability})
if rime_states:
next_state = random.choices(list(rime_states.keys()),
list(rime_states.values()))
current_state = next_state[0]
else:
next_state = random.choices(list(markov_model[current_state].keys()),
list(markov_model[current_state].values()))
current_state = next_state[0]
else:
next_state = random.choices(list(markov_model[current_state].keys()),
list(markov_model[current_state].values()))
current_state = next_state[0]
lyrics += current_state + " " lyrics += current_state + " "
n += 1 n += 1
return lyrics, current_state return lyrics, current_state