Text To Speech

backend/app/analysis/text_parser.py

@@ -0,0 +1,165 @@
+"""
+Custom command to populate text model with definition, examples, and images
+"""
+import string
+import nltk
+import Levenshtein as Lev
+
+
+# Modified Code from Bing library
+def get_sentences(text):
+    """
+    This function, when given a string of words, breaks it apart into individual
+    sentences through markers of sentence breaks and line breaks(\n)
+
+    :param text: str, any text
+    :return: list containing the fragments of the broken down text
+    """
+    # breaks up text by line breaks first
+    lines = [p for p in text.split('\n') if p]
+    sentences = []
+
+    # breaks up each line by sentence markers
+    for line in lines:
+        sentences.extend(nltk.tokenize.sent_tokenize(line))
+
+    return sentences
+
+
+def correct_sentence(given_sent, correct_sent):
+    """
+    Function takes the user's sentence and the correct sentence and compares them to find missing
+    words, the incorrect words, and a grade
+
+    :param given_sent: str, sentence the user types into the text box
+    :param correct_sent: str, the correct sentence that the instructor inputs
+    :return: dictionary with parameters holding the missing words, correct words,
+        word/correctness at each index
+    """
+
+    grade = {}
+
+    # tokenize given_sent and correct_sent and turn them both into lists
+    given_tok = nltk.tokenize.word_tokenize(given_sent.lower().translate(
+        str.maketrans('', '', string.punctuation)))
+    correct_tok = nltk.tokenize.word_tokenize(correct_sent.lower().translate(
+        str.maketrans('', '', string.punctuation)))
+
+    # hold all the correct words and removed every word that is found to hold only
+    # the missing words
+    grade["missing"] = correct_tok.copy()
+
+    for word in given_tok:
+        if grade["missing"].count(word) != 0:
+            # remove the words that the user typed in to get the missing words
+            grade["missing"].remove(word)
+
+
+    grade["incorrect_word_index"] = []
+
+    # True if the user inputs the same sentence as the correct answer
+    grade["isCorrect"] = given_tok == correct_tok
+
+    grade["words"] = []
+
+    index = 0
+    for ind_1, word in enumerate(given_tok):
+        match_found = False
+
+        # loop until the match is found or all words are looked at and no match is found
+        for ind_2, match in enumerate(correct_tok[index:]):
+
+            if word == match:
+                match_found = True
+                match_index = ind_2 + index
+                break
+
+        # if the match is found then the grade is correct, incorrect otherwise
+        # increase match_index by 1 if the match is found
+        if match_found:
+            grade["words"].append({"word": word,
+                            "grade": "correct"})
+            index = match_index + 1
+        else:
+            grade["incorrect_word_index"].append(ind_1)
+            grade["words"].append({"word": word,
+                            "grade": "incorrect"})
+
+    # incorrect indices
+    for word_index in grade["incorrect_word_index"]:
+
+        # find the  most similar word
+        sim_word = most_similar_word(given_tok[word_index], grade["missing"])
+
+        if sim_word is not None:
+            word_grade = correct_words(given_tok[word_index], sim_word)
+            grade["words"][word_index]["word_grade"] = word_grade
+
+    return grade
+
+
+def most_similar_word(word, comparisons):
+    """
+    Take a word and find the most similar word in a given list
+
+    :param word: string with one word
+    :param comparisons: list of words
+    :return: string, most similar word in comparisons to word
+    """
+    min_lev_val = None
+    min_lev_word = None
+
+    # check the missing words and see how similar they are
+    for current_word in comparisons:
+        current_val = Lev.distance(word, current_word)
+
+        # see if the word is less or more similar
+        if min_lev_val is None or min_lev_val > current_val:
+            min_lev_val = current_val
+            min_lev_word = current_word
+
+    # return the most similar word
+    return min_lev_word
+
+
+def correct_words(given_word, correct_word):
+    """
+    Determine which letters in a input word are correct and incorrect
+
+    :param given_word: string with one word, the incorrect word from the user's input
+    :param correct_word: string with one word, the similar word that is correct
+    :return:
+    """
+    grade = {}
+
+    char_missing = []
+
+    char_missing[:0] = correct_word
+
+    # remove the character if the character is there, find out how many are missing
+    for char in given_word:
+        if char_missing.count(char) != 0:
+            char_missing.remove(char)
+
+    grade["missing"] = list(char_missing)
+    grade["letters"] = []
+
+    # for each character, hold whether it is correct or incorrect
+    index = 0
+    for char in given_word:
+        match_found = False
+        for ind_2, match in enumerate(correct_word[index:]):
+
+            if char == match:
+                match_found = True
+                match_index = ind_2 + index
+                break
+        if match_found:
+            grade["letters"].append({"char": char,
+                            "grade": "correct"})
+            index = match_index + 1
+        else:
+            grade["letters"].append({"char": char,
+                            "grade": "incorrect"})
+
+    return grade

backend/app/views.py

@@ -32,7 +32,14 @@
 from .analysis.crosswords import (
     get_crosswords,
 )
-from .quiz_creation.conjugation_quiz import get_quiz_sentences
+from .quiz_creation.conjugation_quiz import (
+    get_quiz_sentences,
+)
+from .analysis.text_parser import (
+    get_sentences,
+    correct_sentence,
+)
+
 
 
 @api_view(['GET'])
@@ -243,3 +250,24 @@ def get_response_quiz_data(request, text_id):
         raise Http404 from text_not_exist
     res = get_quiz_questions(text_obj.content)
     return Response(res)
+
+
+@api_view(['GET'])
+def get_indiv_sentences(request, text_id):
+    """
+    API endpoint for getting the individual sentences from the given text.
+    """
+    text_obj = Text.objects.get(id=text_id)
+    sentences = get_sentences(text_obj.content)
+    res = [{'sentence': sentence} for sentence in sentences]
+    return Response(res)
+
+
+@api_view(['GET'])
+def get_sentence_grade(request, user_sent, actual_sent):
+    """
+    API endpoint for getting the individual sentences from the given text.
+    """
+    graded_sentence = correct_sentence(user_sent, actual_sent)
+
+    return Response(graded_sentence)

backend/config/urls.py

@@ -28,7 +28,10 @@
     get_picturebook_data,
     get_crossword,
     get_quiz_data,
-    text, get_response_quiz_data,
+    text,
+    get_indiv_sentences,
+    get_sentence_grade,
+    get_response_quiz_data,
 )
 
 
@@ -61,6 +64,9 @@ def react_view_path(route, component_name):
     path('api/text/<int:text_id>', text),
     path('api/get_picturebook_prompt/<int:text_id>/<str:part_of_speech>', get_picturebook_prompt),
     path('api/get_picturebook_data', get_picturebook_data),
+    path('api/get_indiv_sentences/<int:text_id>', get_indiv_sentences),
+    path('api/get_sentence_grade/<str:user_sent>/<str:actual_sent>', get_sentence_grade),
+
 
     # View paths
     react_view_path('', 'IndexView'),
@@ -74,4 +80,5 @@ def react_view_path(route, component_name):
     react_view_path('picturebook/<int:textID>/<str:partOfSpeech>', 'PictureBookView'),
     react_view_path('response_quiz/', 'ResponseAllQuizView'),
     react_view_path('response_quiz/<int:textID>/', 'ResponseQuizView'),
+    react_view_path('textToSpeech/<int:textID>', 'TextToSpeech'),
 ]

frontend/src/UILibrary/styles.scss

@@ -8,6 +8,7 @@
 @import '../instructorView/instructorView';
 @import '../flashcard/flashcardView';
 @import '../pictureBookView/pictureBookView';
+@import '../textToSpeech/textToSpeech';
 
 html {
     position: relative;

frontend/src/app.js

@@ -17,6 +17,7 @@ import { PictureBookView } from './pictureBookView/pictureBookView';
 import { CrosswordView } from './crosswordView/crosswordView';
 import { ResponseAllQuizView } from './responseQuizView/responseAllQuizView';
 import { ResponseQuizView } from './responseQuizView/responseQuizView';
+import { TextToSpeech } from './textToSpeech/textToSpeech';
 
 // Import all styles
 import './UILibrary/styles.scss';
@@ -36,4 +37,5 @@ window.app_modules = {
     QuizView,
     ResponseAllQuizView,
     ResponseQuizView,
+    TextToSpeech,
 };

frontend/src/index/index.js

@@ -14,6 +14,7 @@ const QUIZ_TYPES = {
     'Quiz': ['quiz', idLink],
     'Crossword': ['crossword', posLink],
     'Story Generator': ['picturebook', posLink],
+    'TextToSpeech': ['textToSpeech', idLink],
 };
 
 class TextInfo extends React.Component {