def was_there_source_two_or(dataset, narrative, _): questions = [ 'Did you [hear,listen to] [a,an] <S1> or [a,an] <S2>?', 'Have you [heard,listened to] [a,an] <S1> or [a,an] <S2>?' 'Did you [hear,listen to] any <S1> or any <S2>?', 'Have you [heard,listened to] any <S1> or any <S2>?', 'Was there a sound [produced,made] by [a,an] <S1> or a sound [produced,made] by [a,an] <S2>?', # noqa: E501 'Were there any sounds [produced,made] by [a,an] <S1> or any sounds [produced,made] by [a,an] <S2>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question event_1 = str(np.random.choice(dataset['events'])) # sample event source_1 = str(np.random.choice( dataset['sources'][event_1])) # sample source lst_events = [e for e in dataset['events'] if e != event_1] event_2 = str(np.random.choice(lst_events)) # sample event source_2 = str(np.random.choice( dataset['sources'][event_2])) # sample source question = question.replace('<S1>', source_1) # insert source question = question.replace('<S2>', source_2) # insert source question = sanitize_question(question) # correct grammar lst_sources = get_lst_all_sources(dataset, narrative) answer = 'yes' if (source_1 in lst_sources or source_2 in lst_sources) else 'no' return question, answer
def more_than(dataset, narrative, _): questions = [ 'Were there more <S1>s <A1> than <S2>s <A2>?', 'Was the number of [times,instances,occurrences] [a,an] <S1> <A1> more than the number of [times,instances,occurrences] [a,an] <S2> <A2>?', # noqa: E501 '[Comparing,Listening to,Hearing] the sounds of [a,an] <S1> <A1> and [a,an] <S2> <A2>, were there more [times,instances,occurrences] of the former?', # noqa: E501 '[Comparing,Listening to,Hearing] the sounds of [a,an] <S2> <A2> and [a,an] <S1> <A1>, were there more [times,instances,occurrences] of the latter?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) event_1 = str(np.random.choice(lst_events)) # sample event source_1 = str(np.random.choice(dataset['sources'][event_1])) action_1 = str(np.random.choice(dataset['actions'][event_1])) x_lst_events = [e for e in lst_events if e != event_1] assert len(x_lst_events) > 0, 'Question (more_than) illposed.' event_2 = str(np.random.choice(x_lst_events)) # sample event source_2 = str(np.random.choice(dataset['sources'][event_2])) action_2 = str(np.random.choice(dataset['actions'][event_2])) assert event_1 != event_2, 'Question (more_than) illposed.' question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) answer = 'yes' \ if lst_events.count(event_1) > lst_events.count(event_2) \ else 'no' return question, answer
def equal_to(dataset, narrative, _): questions = [ 'Was the number of times [a,an] <S1> <A1> equal to the number of times [a,an] <S2> <A2>?', # noqa: E501 'Was the number of times [a,an] <S1> <A1> the same as the number of times [a,an] <S2> <A2>?', # noqa: E501 'Was there an equal number of times [a,an] <S1> <A1> and [a,an] <S2> <A2>?', # noqa: E501 'Was there the same number of <S1> <A1> and <S2> <A2>?', ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) event_1 = str(np.random.choice(lst_events)) # sample event source_1 = str(np.random.choice(dataset['sources'][event_1])) action_1 = str(np.random.choice(dataset['actions'][event_1])) x_lst_events = [e for e in lst_events if e != event_1] assert len(x_lst_events) > 0, 'Question (equal_to) illposed.' event_2 = str(np.random.choice(x_lst_events)) # sample event source_2 = str(np.random.choice(dataset['sources'][event_2])) action_2 = str(np.random.choice(dataset['actions'][event_2])) assert event_1 != event_2, 'Question (equal_to) illposed.' question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) answer = 'yes' \ if lst_events.count(event_1) == lst_events.count(event_2) \ else 'no' return question, answer
def compare_same_duration_ordinal(dataset, narrative, rel_diff=0.1): questions = [ 'Was the <O1> [sound event,sound] [roughly,approximately] as <D> as the <O2> [sound event,sound]?', # noqa: E501 'Was the <O1> and <O2> [sound events,sounds] [roughly,approximately] as <D>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O1> [sound event,sound] and the <O2> [sound event,sound], were they [roughly,approximately] as <D>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O1> [sound event,sound] and the <O2> [sound event,sound], did they [roughly,approximately] have the same duration?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O1> and <O2> [sound events,sounds], were they [roughly,approximately] as <D>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O1> and <O2> [sound events,sounds], did they [roughly,approximately] have the same duration?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number_1, ordinal_1 = sample_number(len(lst_events)) duration = sample_duration() number_2, ordinal_2 = sample_second_number(len(lst_events), number_1) assert number_1 != number_2, 'Question (compare_same_duration_ordinal) illposed.' question = question.replace('<O1>', ordinal_1) # insert ordinal question = question.replace('<D>', duration) # insert duration question = question.replace('<O2>', ordinal_2) # insert ordinal question = sanitize_question(question) # correct grammar lst_duration = get_lst_durations(narrative) e_1_duration = lst_duration[number_1 - 1] e_2_duration = lst_duration[number_2 - 1] rel_duration_diff = compute_rel_diff(np.array(e_1_duration), np.array(e_2_duration)) # Assert a good margin in relative duration assert np.sum(np.logical_and(rel_duration_diff > rel_diff, rel_duration_diff < (2 * rel_diff))) <= 0, \ 'Question (compare_same_duration_ordinal) illposed.' answer = 'yes' if rel_duration_diff <= rel_diff else 'no' return question, answer
def what_was_loudness(dataset, narrative, rel_diff=0.1): questions = [ 'What was the <AL> sound?', 'What was the <AL> sound you [heard,listened to]?', 'What was the <AL> sound that you [heard,listened to]?', 'What was the <AL> sound that was heard?', ] question = str(np.random.choice(questions)) # sample question loudness = sample_absolute_loudness() question = question.replace('<AL>', loudness) # insert loudness question = sanitize_question(question) # correct grammar lst_events = get_lst_events(narrative) lst_loudness = get_lst_loudness(narrative) if 'loud' in question: est = np.argmax(lst_loudness) elif 'quiet' in question: est = np.argmin(lst_loudness) else: assert False, \ 'Loudness illdefined in Question (what_was_loudness).' # Assert a good margin in relative loudness evt_loudness = lst_loudness[est] x_loudness = [j for i, j in enumerate(lst_loudness) if i != est] rel_loudness_diff = compute_rel_diff(np.array(x_loudness), np.array(evt_loudness)) assert np.sum(rel_loudness_diff < rel_diff) <= 0, \ 'Question (what_was_loudness) illposed.' e = lst_events[est] answer = (str(np.random.choice(dataset['sources'][e])) + ' ' + str(np.random.choice(dataset['actions'][e]))) return question, answer
def how_many_event_two(dataset, narrative, _): questions = ['How many times was [a,an] <S1> <A1> [or,and] [a,an] <S2> <A2>?', 'How many times did you [hear,listen to] [a,an] <S1> <A1> [or,and] [a,an] <S2> <A2>?', # noqa: E501 'How many times have you [heard,listened to] [a,an] <S1> <A1> [or,and] [a,an] <S2> <A2>?', # noqa: E501 'What is the number of times [a,an] <S1> <A1> [or,and] [a,an] <S2> <A2>?', # noqa: E501 'What is the number of times did you [hear,listen to] [a,an] <S1> <A1> [or,and] [a,an] <S2> <A2>?', # noqa: E501 'What is the number of times you [heard,listened to] [a,an] <S1> <A1> [or,and] [a,an] <S2> <A2>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question event_1 = str(np.random.choice(dataset['events'])) # sample event source_1 = str(np.random.choice(dataset['sources'][event_1])) action_1 = str(np.random.choice(dataset['actions'][event_1])) x_lst_events = [e for e in dataset['events'] if e != event_1] event_2 = str(np.random.choice(x_lst_events)) # sample event source_2 = str(np.random.choice(dataset['sources'][event_2])) action_2 = str(np.random.choice(dataset['actions'][event_2])) assert event_1 != event_2, 'Question (how_many_event_two) illposed.' question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) # correct grammar lst_events = get_lst_events(narrative) answer = numbers_to_words(lst_events.count(event_1) + lst_events.count(event_2)) return question, answer
def what_was_duration_relative(dataset, narrative, rel_diff=0.1): questions = [ 'What was the <AD> sound <RO> the <S> <A>?', 'What was the <AD> sound <RO> [hearing,listening to] the <S> <A>?', 'What was the <AD> sound <RO> the <S> <A> was heard?', ] question = str(np.random.choice(questions)) # sample question duration = sample_absolute_duration() preposition = sample_preposition() lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (what_was_duration_relative) illposed.' event = str(np.random.choice(unique_lst_events)) source = str(np.random.choice(dataset['sources'][event])) # sample source action = str(np.random.choice(dataset['actions'][event])) # sample action question = question.replace('<AD>', duration) # insert duration question = question.replace('<RO>', preposition) # insert preposition question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = sanitize_question(question) # correct grammar assert lst_events.count(event) == 1, \ 'Question (what_was_duration_relative) illposed.' lst_durations = get_lst_durations(narrative) event_idx = lst_events.index(event) if 'before' in question: lst_events_e = lst_events[:event_idx] lst_events_d = lst_durations[:event_idx] elif 'after' in question: lst_events_e = lst_events[(event_idx + 1):] lst_events_d = lst_durations[(event_idx + 1):] else: assert False, \ 'Preposition illdefined in Question (what_was_duration_relative).' assert len(lst_events_e) > 0, \ 'Question (what_was_duration_relative) illposed.' if 'long' in question: est = np.argmax(lst_events_d) elif 'short' in question: est = np.argmin(lst_events_d) else: assert False, \ 'Duration illdefined in Question (what_was_duration_relative).' # Assert a good margin in relative duration evt_duration = lst_events_d[est] x_durations = [j for i, j in enumerate(lst_events_d) if i != est] rel_duration_diff = compute_rel_diff(np.array(x_durations), np.array(evt_duration)) assert np.sum(rel_duration_diff < rel_diff) <= 0, \ 'Question (what_was_duration_relative) illposed.' e = lst_events_e[est] answer = (str(np.random.choice(dataset['sources'][e])) + ' ' + str(np.random.choice(dataset['actions'][e]))) return question, answer
def what_was_duration_relative_ordinal(dataset, narrative, rel_diff=0.1): questions = [ 'What was the <AD> sound <RO> the <O> sound?', 'What was the <AD> sound <RO> [hearing,listening to] the <O> sound?', 'What was the <AD> sound <RO> the <O> sound was heard?', ] question = str(np.random.choice(questions)) # sample question duration = sample_absolute_duration() preposition = sample_preposition() lst_events = get_lst_events(narrative) number, ordinal = sample_number(len(lst_events)) question = question.replace('<AD>', duration) # insert duration question = question.replace('<RO>', preposition) # insert preposition question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar lst_durations = get_lst_durations(narrative) event_idx = (number - 1) answer = None if 'before' in question: if (event_idx - 1) < 0: answer = 'nothing' else: lst_events_e = lst_events[:event_idx] lst_events_d = lst_durations[:event_idx] elif 'after' in question: if (event_idx + 1) >= len(lst_events): answer = 'nothing' else: lst_events_e = lst_events[(event_idx + 1):] lst_events_d = lst_durations[(event_idx + 1):] else: assert False, \ 'Preposition illdefined in Question (what_was_duration_relative_ordinal).' if answer is None: assert len(lst_events_e) > 0, \ 'Question (what_was_duration_relative_ordinal) illposed.' if 'long' in question: est = np.argmax(lst_events_d) elif 'short' in question: est = np.argmin(lst_events_d) else: assert False, \ 'Duration illdefined in Question (what_was_duration_relative_ordinal).' # Assert a good margin in relative duration evt_duration = lst_events_d[est] x_durations = [j for i, j in enumerate(lst_events_d) if i != est] rel_duration_diff = compute_rel_diff(np.array(x_durations), np.array(evt_duration)) assert np.sum(rel_duration_diff < rel_diff) <= 0, \ 'Question (what_was_duration_relative_ordinal) illposed.' e = lst_events_e[est] answer = (str(np.random.choice(dataset['sources'][e])) + ' ' + str(np.random.choice(dataset['actions'][e]))) return question, answer
def was_there_immediate_relative(dataset, narrative, _): questions = [ 'Did you [hear,listen to] [a,an] <S1> <A1> <IO> the <S2> <A2>?', # noqa: E501 'Have you [heard,listened to] [a,an] <S1> <A1> <IO> the <S2> <A2>?', # noqa: E501 'Did you [hear,listen to] any <S1> <A1> <IO> the <S2> <A2>?', 'Have you [heard,listened to] any <S1> <A1> <IO> the <S2> <A2>?', 'Was there [a,an] <S1> <A1> <IO> the <S2> <A2>?', 'Were there any <S1>s <A1> <IO> the <S2> <A2>?', 'Did you [hear,listen to] a sound that [sounds like,sounded like,is,was] [a,an] <S1> <A1> <IO> the <S2> <A2>?', # noqa: E501 '<IO> the <S2> <A2>, did you [hear,listen to] [a,an] <S1> <A1> ?', # noqa: E501 '<IO> the <S2> <A2>, did you [hear,listen to] any <S1> <A1>?', '<IO> the <S2> <A2>, was there [a,an] <S1> <A1>?', '<IO> the <S2> <A2>, were there any <S1>s <A1>?', '<IO> the <S2> <A2>, did you [hear,listen to] a sound that [sounds like,sounded like,is,was] [a,an] <S1> <A1>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question event_1 = str(np.random.choice(dataset['events'])) # sample event source_1 = str(np.random.choice(dataset['sources'][event_1])) action_1 = str(np.random.choice(dataset['actions'][event_1])) preposition = sample_immediate_preposition() lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] unique_lst_events = [e for e in unique_lst_events if e != event_1] assert len(unique_lst_events) > 0, \ 'Question (was_there_immediate_relative) illposed.' event_2 = str(np.random.choice(unique_lst_events)) source_2 = str(np.random.choice(dataset['sources'][event_2])) action_2 = str(np.random.choice(dataset['actions'][event_2])) question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<IO>', preposition) # insert preposition question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) # correct grammar assert lst_events.count(event_2) == 1, \ 'Question (was_there_immediate_relative) illposed.' event_2_idx = lst_events.index(event_2) if 'before' in preposition: if (event_2_idx - 1) < 0: target_event = [] else: target_event = lst_events[event_2_idx - 1] elif 'after' in preposition: if (event_2_idx + 1) >= len(lst_events): target_event = [] else: target_event = lst_events[event_2_idx + 1] else: assert False, \ 'Preposition illdefined in Question (was_there_immediate_relative).' answer = 'yes' if event_1 == target_event else 'no' return question, answer
def what_was_relative(dataset, narrative, _): questions = [ 'What was the sound <RO> the <S> <A>?', 'What was the sound <RO> [hearing,listening to] the <S> <A>?', 'What was the sound <RO> the <S> <A> was heard?', 'What did you [hear,listen to] <RO> the <S> <A>?', 'What did you [hear,listen to] <RO> [hearing,listening to] the <S> <A>?', # noqa: E501 'What did you [hear,listen to] <RO> the <S> <A> was heard?', 'What was the sound <IO> the <S> <A>?', 'What was the sound <IO> [hearing,listening to] the <S> <A>?', 'What was the sound <IO> the <S> <A> was heard?', 'What did you [hear,listen to] <IO> the <S> <A>?', 'What did you [hear,listen to] <IO> [hearing,listening to] the <S> <A>?', # noqa: E501 'What did you [hear,listen to] <IO> the <S> <A> was heard?', ] question = str(np.random.choice(questions)) # sample question preposition = sample_preposition() immediate_preposition = sample_immediate_preposition() lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (what_was_relative) illposed.' event = str(np.random.choice(unique_lst_events)) source = str(np.random.choice(dataset['sources'][event])) # sample source action = str(np.random.choice(dataset['actions'][event])) # sample action # Only one of the following two lines will have an effect question = question.replace('<RO>', preposition) # insert preposition question = question.replace('<IO>', immediate_preposition) question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = sanitize_question(question) # correct grammar assert lst_events.count(event) == 1, \ 'Question (what_was_relative) illposed.' event_idx = lst_events.index(event) if 'before' in question: if (event_idx - 1) < 0: answer = 'nothing' else: e = lst_events[event_idx - 1] answer = (str(np.random.choice(dataset['sources'][e])) + ' ' + str(np.random.choice(dataset['actions'][e]))) elif 'after' in question: if (event_idx + 1) >= len(lst_events): answer = 'nothing' else: e = lst_events[event_idx + 1] answer = (str(np.random.choice(dataset['sources'][e])) + ' ' + str(np.random.choice(dataset['actions'][e]))) else: assert False, 'Preposition illdefined in Question (what_was_relative).' return question, answer
def compare_duration(dataset, narrative, rel_diff=0.1): questions = [ 'Was the <S1> <A1> <RD> than the <S2> <A2>?', 'Was the sound of the <S1> <A1> <RD> than the sound of the <S2> <A2>?', # noqa: E501 '[Comparing,Listening to,Hearing] the sound of the <S1> <A1> and the sound of the <S2> <A2>, was the former <RD>?', # noqa: E501 '[Comparing,Listening to,Hearing] the sounds of the <S1> <A1> and the <S2> <A2>, was the former <RD>?', # noqa: E501 '[Comparing,Listening to,Hearing] the sound of the <S2> <A2> and the sound of the <S1> <A1>, was the latter <RD>?', # noqa: E501 '[Comparing,Listening to,Hearing] the sounds of the <S2> <A2> and the <S1> <A1>, was the latter <RD>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (compare_duration) illposed.' event_1 = str(np.random.choice(unique_lst_events)) # sample event source_1 = str(np.random.choice(dataset['sources'][event_1])) action_1 = str(np.random.choice(dataset['actions'][event_1])) rel_duration = sample_rel_duration() x_unique_lst_events = [e for e in unique_lst_events if e != event_1] assert len(x_unique_lst_events) > 0, \ 'Question (compare_duration) illposed.' event_2 = str(np.random.choice(x_unique_lst_events)) # sample event source_2 = str(np.random.choice(dataset['sources'][event_2])) action_2 = str(np.random.choice(dataset['actions'][event_2])) assert lst_events.count(event_1) == 1, \ 'Question (compare_duration) illposed.' assert lst_events.count(event_2) == 1, \ 'Question (compare_duration) illposed.' assert event_1 != event_2, 'Question (compare_duration) illposed.' question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<RD>', rel_duration) # insert duration question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) lst_duration = get_lst_durations(narrative) e_1_duration = lst_duration[lst_events.index(event_1)] e_2_duration = lst_duration[lst_events.index(event_2)] # Assert a good margin in relative duration rel_duration_diff = compute_rel_diff(np.array(e_1_duration), np.array(e_2_duration)) assert np.sum(rel_duration_diff < rel_diff) <= 0, \ 'Question (compare_duration) illposed.' if 'short' in question: answer = 'yes' if e_1_duration < e_2_duration else 'no' elif 'long' in question: answer = 'yes' if e_1_duration > e_2_duration else 'no' else: assert False, 'Duration illdefined in Question (compare_duration).' return question, answer
def compare_same_duration(dataset, narrative, rel_diff=0.1): questions = [ 'Was the <S1> <A1> [roughly,approximately] as <D> as the <S2> <A2>?', # noqa: E501 'Was the sound of the <S1> <A1> [roughly,approximately] as <D> as the sound of the <S2> <A2>?', # noqa: E501 'Was the sound of the <S1> <A1> [roughly,approximately] the same duration as the sound of the <S2> <A2>?', # noqa: E501 '[Comparing,Listening to,Hearing] the sound of the <S1> <A1> and the sound of the <S2> <A2>, did they [roughly,approximately] have the same duration?', # noqa: E501 '[Comparing,Listening to,Hearing] the sounds of the <S1> <A1> and the <S2> <A2>, did they [roughly,approximately] have the same duration?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (compare_same_duration) illposed.' event_1 = str(np.random.choice(unique_lst_events)) # sample event source_1 = str(np.random.choice(dataset['sources'][event_1])) action_1 = str(np.random.choice(dataset['actions'][event_1])) duration = sample_duration() x_unique_lst_events = [e for e in unique_lst_events if e != event_1] assert len(x_unique_lst_events) > 0, \ 'Question (compare_same_duration) illposed.' event_2 = str(np.random.choice(x_unique_lst_events)) # sample event source_2 = str(np.random.choice(dataset['sources'][event_2])) action_2 = str(np.random.choice(dataset['actions'][event_2])) assert lst_events.count(event_1) == 1, \ 'Question (compare_same_duration) illposed.' assert lst_events.count(event_2) == 1, \ 'Question (compare_same_duration) illposed.' assert event_1 != event_2, 'Question (compare_same_duration) illposed.' question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<D>', duration) # insert duration question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) lst_duration = get_lst_durations(narrative) e_1_duration = lst_duration[lst_events.index(event_1)] e_2_duration = lst_duration[lst_events.index(event_2)] rel_duration_diff = compute_rel_diff(np.array(e_1_duration), np.array(e_2_duration)) # Assert a good margin in relative duration assert np.sum(np.logical_and(rel_duration_diff > rel_diff, rel_duration_diff < (2 * rel_diff))) <= 0, \ 'Question (compare_same_duration) illposed.' answer = 'yes' if rel_duration_diff <= rel_diff else 'no' return question, answer
def compare_same_duration_event_ordinal(dataset, narrative, rel_diff=0.1): questions = [ 'Was the <S> <A> [roughly,approximately] as <D> as the <O> [sound event,sound]?', # noqa: E501 '[Comparing,Listening to,Hearing] the <S> <A> and the <O> [sound event,sound], were they [roughly,approximately] as <D>?', # noqa: E501 '[Comparing,Listening to,Hearing] the sound of the <S> <A> and the <O> [sound event,sound], were they [roughly,approximately] as <D>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <S> <A> and the <O> [sound event,sound], did they [roughly,approximately] have the same duration?', # noqa: E501 '[Comparing,Listening to,Hearing] the sound of the <S> <A> and the <O> [sound event,sound], did they [roughly,approximately] have the same duration?', # noqa: E501 'Was the <O> [sound event,sound] [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O> [sound event,sound] and the <S> <A>, were they [roughly,approximately] as <D>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O> [sound event,sound] and the sound of the <S> <A>, were they [roughly,approximately] as <D>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O> [sound event,sound] and the <S> <A>, did they [roughly,approximately] have the same duration?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O> [sound event,sound] and the sound of the <S> <A>, did they [roughly,approximately] have the same duration?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (compare_same_duration_event_ordinal) illposed.' event = str(np.random.choice(unique_lst_events)) # sample event source = str(np.random.choice(dataset['sources'][event])) action = str(np.random.choice(dataset['actions'][event])) duration = sample_duration() number, ordinal = sample_second_number(len(lst_events), lst_events.index(event) + 1) assert lst_events.count(event) == 1, \ 'Question (compare_same_duration_event_ordinal) illposed.' assert lst_events.index(event) != (number - 1), \ 'Question (compare_same_duration_event_ordinal) illposed.' question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = question.replace('<D>', duration) # insert duration question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar lst_duration = get_lst_durations(narrative) e_1_duration = lst_duration[lst_events.index(event)] e_2_duration = lst_duration[number - 1] rel_duration_diff = compute_rel_diff(np.array(e_1_duration), np.array(e_2_duration)) # Assert a good margin in relative duration assert np.sum(np.logical_and(rel_duration_diff > rel_diff, rel_duration_diff < (2 * rel_diff))) <= 0, \ 'Question (compare_same_duration_event_ordinal) illposed.' answer = 'yes' if rel_duration_diff <= rel_diff else 'no' return question, answer
def how_many_sounds_duration_event(dataset, narrative, rel_diff=0.1): questions = ['How many [sound events,sounds] [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'How many [sound events,sounds] that are [roughly,approximately] as <D> as the <S> <A> [did,could] you [hear,listen to]?', # noqa: E501 'How many [sound events,sounds] that are [roughly,approximately] as <D> as the <S> <A> have you heard?', # noqa: E501 'How many [sound events,sounds] that have [roughly,approximately] the same duration as the <S> <A>?', # noqa: E501 'How many [sound events,sounds] that have [roughly,approximately] the same duration as the <S> <A> [did,could] you [hear,listen to]?', # noqa: E501 'How many [sound events,sounds] that have [roughly,approximately] the same duration as the <S> <A> have you heard?', # noqa: E501 'What is the number of [sound events,sounds] [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'What is the number of [sound events,sounds] that are [roughly,approximately] as <D> as the <S> <A> [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of [sound events,sounds] that are [roughly,approximately] as <D> as the <S> <A> have you heard?', # noqa: E501 'What is the number of [sound events,sounds] that have [roughly,approximately] the same duration as the <S> <A>?', # noqa: E501 'What is the number of [sound events,sounds] that have [roughly,approximately] the same duration as the <S> <A> [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of [sound events,sounds] that have [roughly,approximately] the same duration as the <S> <A> have you heard?', # noqa: E501 'There is [a,an] <S> <A>; how many [sound events,sounds] that are [roughly,approximately] as <D>?', # noqa: E501 'There is [a,an] <S> <A>; what is the number of [sound events,sounds] that are [roughly,approximately] as <D>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question duration = sample_duration() # sample duration lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (how_many_sounds_duration_event) illposed.' event = str(np.random.choice(unique_lst_events)) source = str(np.random.choice(dataset['sources'][event])) # sample source action = str(np.random.choice(dataset['actions'][event])) # sample action question = question.replace('<D>', duration) # insert duration question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = sanitize_question(question) # correct grammar assert lst_events.count(event) == 1, \ 'Question (how_many_sounds_duration_event) illposed.' lst_durations = get_lst_durations(narrative) event_idx = lst_events.index(event) evt_duration = lst_durations[event_idx] x_durations = [j for i, j in enumerate(lst_durations) if i != event_idx] rel_durations_diff = compute_rel_diff(np.array(x_durations), np.array(evt_duration)) # Assert a good margin in relative loudness assert np.sum(np.logical_and(rel_durations_diff > rel_diff, rel_durations_diff < (2 * rel_diff))) <= 0, \ 'Question (how_many_sounds_duration_event) illposed.' answer = numbers_to_words(np.sum(rel_durations_diff <= rel_diff)) return question, answer
def compare_duration_ordinal_event(dataset, narrative, rel_diff=0.1): questions = [ 'Was the <O> [sound event,sound] <RD> than the <S> <A>?', 'Was the <O> [sound event,sound] <RD> than the sound of the <S> <A>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O> [sound event,sound] and the <S> <A>, was the former <RD>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <S> <A> and the <O> [sound event,sound], was the latter <RD>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (compare_duration_ordinal_event) illposed.' event = str(np.random.choice(unique_lst_events)) # sample event source = str(np.random.choice(dataset['sources'][event])) action = str(np.random.choice(dataset['actions'][event])) rel_duration = sample_rel_duration() number, ordinal = sample_second_number(len(lst_events), lst_events.index(event) + 1) assert lst_events.count(event) == 1, \ 'Question (compare_duration_ordinal_event) illposed.' assert lst_events.index(event) != (number - 1), \ 'Question (compare_duration_ordinal_event) illposed.' question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = question.replace('<RD>', rel_duration) # insert duration question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar lst_duration = get_lst_durations(narrative) e_1_duration = lst_duration[number - 1] e_2_duration = lst_duration[lst_events.index(event)] # Assert a good margin in relative duration rel_duration_diff = compute_rel_diff(np.array(e_1_duration), np.array(e_2_duration)) assert np.sum(rel_duration_diff < rel_diff) <= 0, \ 'Question (compare_duration_ordinal_event) illposed.' if 'short' in question: answer = 'yes' if e_1_duration < e_2_duration else 'no' elif 'long' in question: answer = 'yes' if e_1_duration > e_2_duration else 'no' else: assert False, \ 'Duration illdefined in Question (compare_duration_ordinal_event).' return question, answer
def was_there_similar_duration(dataset, narrative, rel_diff=0.1): questions = [ 'Were there any sounds [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Were there any sounds that were [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Were there any sounds that were [roughly,approximately] the same duration as the <S> <A>?', # noqa: E501 'Was there any sound [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Was there any sound that was [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Was there any sound that was [roughly,approximately] the same duration as the <S> <A>?', # noqa: E501 'Was there at least a sound [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Was there at least a sound that was [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Was there at least a sound that was [roughly,approximately] the same duration as <S> <A>?', # noqa: E501 'Was there at least [one,a single] sound [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Was there at least [one,a single] sound that was [roughly,approximately] as <D> as the <S> <A>?', # noqa: E501 'Was there at least [one,a single] sound that was [roughly,approximately] the same duration as <S> <A>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question duration = sample_duration() # sample duration lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (was_there_similar_duration) illposed.' event = str(np.random.choice(unique_lst_events)) source = str(np.random.choice(dataset['sources'][event])) # sample source action = str(np.random.choice(dataset['actions'][event])) # sample action question = question.replace('<D>', duration) # insert duration question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = sanitize_question(question) # correct grammar assert lst_events.count(event) == 1, \ 'Question (was_there_similar_duration) illposed.' lst_durations = get_lst_durations(narrative) event_idx = lst_events.index(event) evt_duration = lst_durations[event_idx] x_durations = [j for i, j in enumerate(lst_durations) if i != event_idx] rel_durations_diff = compute_rel_diff(np.array(x_durations), np.array(evt_duration)) # Assert a good margin in relative duration assert np.sum(np.logical_and(rel_durations_diff > rel_diff, rel_durations_diff < (2 * rel_diff))) <= 0, \ 'Question (was_there_similar_duration) illposed.' answer = 'yes' if np.sum(rel_durations_diff <= rel_diff) >= 1 else 'no' return question, answer
def how_many_event_relative(dataset, narrative, _): questions = ['How many <S1>s <A1> <RO> the <S2> <A2> were there?', 'How many <S1>s <A1> <RO> the <S2> <A2> [did,could] you [hear,listen to]?', # noqa: E501 'How many <S1>s <A1> <RO> the <S2> <A2> have you [heard,listened to]?', # noqa: E501 'What is the number of <S1>s <A1> <RO> the <S2> <A2>?', 'What is the number of <S1>s <A1> <RO> the <S2> <A2> [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of <S1>s <A1> <RO> the <S2> <A2> have you [heard,listened to]?', # noqa: E501 'There is [a,an] <S2> <A2>; how many <S1>s <A1> [did,could] you hear <RO>?', # noqa: E501 'There is [a,an] <S2> <A2>; how many <S1>s <A1> have you heard <RO>?', # noqa: E501 'There is [a,an] <S2> <A2>; what is the number of <S1>s <A1> [did,could] you hear <RO>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question event_1 = str(np.random.choice(dataset['events'])) # sample event source_1 = str(np.random.choice(dataset['sources'][event_1])) action_1 = str(np.random.choice(dataset['actions'][event_1])) preposition = sample_preposition() lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] unique_lst_events = [e for e in unique_lst_events if e != event_1] assert len(unique_lst_events) > 0, \ 'Question (how_many_event_relative) illposed.' event_2 = str(np.random.choice(unique_lst_events)) source_2 = str(np.random.choice(dataset['sources'][event_2])) action_2 = str(np.random.choice(dataset['actions'][event_2])) question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<RO>', preposition) # insert preposition question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) # correct grammar assert lst_events.count(event_2) == 1, \ 'Question (how_many_event_relative) illposed.' event_2_idx = lst_events.index(event_2) if 'before' in question: lst_events_e = lst_events[:event_2_idx] elif 'after' in question: lst_events_e = lst_events[(event_2_idx + 1):] else: assert False, \ 'Relative preposition illdefined in Question (how_many_event_relative).' answer = numbers_to_words(lst_events_e.count(event_1)) return question, answer
def how_many(dataset, narrative, _): questions = ['How many [sound events,sounds] were there?', 'How many [sound events,sounds] [did,could] you [hear,listen to]?', 'How many [sound events,sounds] have you [heard,listened to]?', 'What is the number of [sound events,sounds]?', 'What is the number of [sound events,sounds] [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of [sound events,sounds] have you [heard,listened to]?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question question = sanitize_question(question) # correct grammar lst_events = get_lst_events(narrative) answer = numbers_to_words(len(lst_events)) return question, answer
def how_many_ordinal(dataset, narrative, _): questions = ['How many times did you [hear,listen to] a sound that [sounded,seemed] like the <O> [sound event,sound]?', # noqa: E501 'What is the number of times did you [hear,listen to] a sound that [sounded,seemed] like the <O> [sound event,sound]?', # noqa: E501 '[Hearing,Listening to] the <O> [sound event,sound], how many sounds were [the same, similar]?', # noqa: E501 '[Hearing,Listening to] the <O> [sound event,sound], what is the number of sounds that were [the same, similar]?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number, ordinal = sample_number(len(lst_events)) question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar event = lst_events[number - 1] answer = numbers_to_words(lst_events.count(event) - 1) # -1 for base event return question, answer
def what_was(dataset, narrative, _): questions = [ 'What was the <O> sound you [heard,listened to]?', 'What was the <O> sound?', 'What did the <O> sound [sound,seem] like?', ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number, ordinal = sample_number(len(lst_events)) question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar event = lst_events[number - 1] answer = (str(np.random.choice(dataset['sources'][event])) + ' ' + str(np.random.choice(dataset['actions'][event]))) return question, answer
def how_many_sounds_relative(dataset, narrative, _): questions = ['How many [sound events,sounds] <RO> the <S> <A> were there?', 'How many [sound events,sounds] <RO> the <S> <A> [did,could] you [hear,listen to]?', # noqa: E501 'How many [sound events,sounds] <RO> the <S> <A> have you [heard,listened to]?', # noqa: E501 'What is the number of [sound events,sounds] <RO> the <S> <A>?', 'What is the number of [sound events,sounds] <RO> the <S> <A> [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of [sound events,sounds] <RO> the <S> <A> have you [heard,listened to]?', # noqa: E501 'There is [a,an] <S> <A>; how many [sound events,sounds] [did,could] you hear <RO>?', # noqa: E501 'There is [a,an] <S> <A>; how many [sound events,sounds] have you heard <RO>?', # noqa: E501 'There is [a,an] <S> <A>; what is the number of [sound events,sounds] [did,could] you hear <RO>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question preposition = sample_preposition() lst_events = get_lst_events(narrative) unique_lst_events = [e for e in lst_events if lst_events.count(e) == 1] assert len(unique_lst_events) > 0, \ 'Question (how_many_sounds_relative) illposed.' event = str(np.random.choice(unique_lst_events)) source = str(np.random.choice(dataset['sources'][event])) # sample source action = str(np.random.choice(dataset['actions'][event])) # sample action question = question.replace('<RO>', preposition) # insert preposition question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = sanitize_question(question) # correct grammar assert lst_events.count(event) == 1, \ 'Question (how_many_sounds_relative) illposed.' event_idx = lst_events.index(event) if 'before' in question: lst_events_e = lst_events[:event_idx] elif 'after' in question: lst_events_e = lst_events[(event_idx + 1):] else: assert False, \ 'Preposition illdefined in Question (how_many_sounds_relative).' answer = numbers_to_words(len(lst_events_e)) return question, answer
def was_there_similar_ordinal(dataset, narrative, _): questions = [ 'Were there any similar sounds to the <O> sound?', 'Were there any sounds that were similar to the <O> sound?', 'Was there at least a sound similar to the <O> sound?', 'Was there at least a sound that was similar to the <O> sound?', # noqa: E501 'Was there at least [one,a single] sound similar to the <O> sound?', 'Was there at least [one,a single] sound that was similar to the <O> sound?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number, ordinal = sample_number(len(lst_events)) question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar event = lst_events[number - 1] answer = 'yes' if lst_events.count(event) > 1 else 'no' # 1 for reference return question, answer
def was_there_source(dataset, narrative, _): questions = [ 'Did you [hear,listen to] [a,an] <S>?', 'Have you [heard,listened to] [a,an] <S>?' 'Did you [hear,listen to] any <S>?', 'Have you [heard,listened to] any <S>?', 'Was there a sound [produced,made] by [a,an] <S>?', 'Were there any sounds [produced,made] by [a,an] <S>?', ] question = str(np.random.choice(questions)) # sample question event = str(np.random.choice(dataset['events'])) # sample event source = str(np.random.choice(dataset['sources'][event])) # sample source question = question.replace('<S>', source) # insert source question = sanitize_question(question) # correct grammar answer = 'yes' if source in get_lst_all_sources(dataset, narrative) else 'no' return question, answer
def how_many_sounds_relative_ordinal(dataset, narrative, _): questions = ['How many [sound events,sounds] after the <O> [sound event,sound] were there?', # noqa: E501 'How many [sound events,sounds] after the <O> [sound event,sound] [did,could] you [hear,listen to]?', # noqa: E501 'How many [sound events,sounds] after the <O> [sound event,sound] have you [heard,listened to]?', # noqa: E501 'What is the number of [sound events,sounds] after the <O> [sound event,sound]?', # noqa: E501 'What is the number of [sound events,sounds] after the <O> [sound event,sound] [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of [sound events,sounds] after the <O> [sound event,sound] have you [heard,listened to]?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number, ordinal = sample_number(len(lst_events)) question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar assert number < (len(lst_events) - 1), \ 'Question (how_many_sounds_relative_ordinal) illposed.' lst_events_e = lst_events[number:] answer = numbers_to_words(len(lst_events_e)) return question, answer
def how_many_event(dataset, narrative, _): questions = ['How many times was [a,an] <S> <A>?', 'How many times did you [hear,listen to] [a,an] <S> <A>?', 'How many times have you [heard,listened to] [a,an] <S> <A>?', 'What is the number of times [a,an] <S> <A>?', 'What is the number of times did you [hear,listen to] [a,an] <S> <A>?', # noqa: E501 'What is the number of times you [heard,listened to] [a,an] <S> <A>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) event = str(np.random.choice(lst_events)) source = str(np.random.choice(dataset['sources'][event])) # sample source action = str(np.random.choice(dataset['actions'][event])) # sample action question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = sanitize_question(question) # correct grammar answer = numbers_to_words(lst_events.count(event)) return question, answer
def compare_ordinal(dataset, narrative, _): questions = [ 'Was the <O1> [sound event,sound] [the same as,similar to] the <O2> [sound event,sound]?', # noqa: E501 'Was the <O1> [sound event,sound] and <O2> [sound event,sound] [the same,similar]?', # noqa: E501 'Were the <O1> and <O2> [sound events,sounds] [the same,similar]?', ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number_1, ordinal_1 = sample_number(len(lst_events)) number_2, ordinal_2 = sample_second_number(len(lst_events), number_1) assert number_1 != number_2, 'Question (compare_ordinal) illposed.' question = question.replace('<O1>', ordinal_1) # insert ordinal question = question.replace('<O2>', ordinal_2) # insert ordinal question = sanitize_question(question) # correct grammar answer = 'yes' if lst_events[number_1 - 1] == lst_events[number_2 - 1] \ else 'no' return question, answer
def was_there_two_or(dataset, narrative, _): questions = [ 'Did you [hear,listen to] [a,an] <S1> <A1> or [a,an] <S2> <A2>?', 'Have you [heard,listened to] [a,an] <S1> <A1> or [a,an] <S2> <A2>?', 'Did you [hear,listen to] any <S1> <A1> or any <S2> <A2>?', 'Have you [heard,listened to] any <S1> <A1> or any <S2> <A2>?', 'Did you [hear,listen to] a sound that [sounds like,is] [a,an] <S1> <A1> or a sound [sounds like,is] [a,an] <S2> <A2>?', # noqa: E501 'Did you [hear,listen to] a sound that [sounded like,was] [a,an] <S1> <A1> or a sound [sounded like,was] [a,an] <S2> <A2>?', # noqa: E501 'Have you [heard,listened to] a sound that [sounds like,is] [a,an] <S1> <A1> or a sound [sounds like,is] [a,an] <S2> <A2>?', # noqa: E501 'Have you [heard,listened to] a sound that [sounded like,was] [a,an] <S1> <A1> or a sound [sounded like,was] [a,an] <S2> <A2>?', # noqa: E501 'Was there [a,an] <S1> <A1> or [a,an] <S2> <A2>?', 'Were there any <S1>s <A1> or any <S2>s <A2>?', ] question = str(np.random.choice(questions)) # sample question event_1 = str(np.random.choice(dataset['events'])) # sample event source_1 = str(np.random.choice( dataset['sources'][event_1])) # sample source action_1 = str(np.random.choice( dataset['actions'][event_1])) # sample action lst_events = [e for e in dataset['events'] if e != event_1] event_2 = str(np.random.choice(lst_events)) # sample event source_2 = str(np.random.choice( dataset['sources'][event_2])) # sample source action_2 = str(np.random.choice( dataset['actions'][event_2])) # sample action question = question.replace('<S1>', source_1) # insert source question = question.replace('<A1>', action_1) # insert action question = question.replace('<S2>', source_2) # insert source question = question.replace('<A2>', action_2) # insert action question = sanitize_question(question) # correct grammar lst_events = get_lst_events(narrative) answer = 'yes' if (event_1 in lst_events or event_2 in lst_events) else 'no' return question, answer
def how_many_sounds_duration_ordinal(dataset, narrative, rel_diff=0.1): questions = ['How many [sound events,sounds] [roughly,approximately] as <D> as the <O> sound?', # noqa: E501 'How many [sound events,sounds] that are [roughly,approximately] as <D> as the <O> sound?', # noqa: E501 'How many [sound events,sounds] that are [roughly,approximately] as <D> as the <O> sound [did,could] you [hear,listen to]?', # noqa: E501 'How many [sound events,sounds] that are [roughly,approximately] as <D> as the <O> sound have you heard?', # noqa: E501 'How many [sound events,sounds] that have [roughly,approximately] the same duration as the <O> sound?', # noqa: E501 'How many [sound events,sounds] that have [roughly,approximately] the same duration as the <O> sound [did,could] you [hear,listen to]?', # noqa: E501 'How many [sound events,sounds] that have [roughly,approximately] the same duration as the <O> sound have you heard?', # noqa: E501 'What is the number of [sound events,sounds] [roughly,approximately] as <D> as the <O> sound?', # noqa: E501 'What is the number of [sound events,sounds] that are [roughly,approximately] as <D> as the <O> sound?', # noqa: E501 'What is the number of [sound events,sounds] that are [roughly,approximately] as <D> as the <O> sound [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of [sound events,sounds] that are [roughly,approximately] as <D> as the <O> sound have you heard?', # noqa: E501 'What is the number of [sound events,sounds] that have [roughly,approximately] the same duration as the <O> sound?', # noqa: E501 'What is the number of [sound events,sounds] that have [roughly,approximately] the same duration as the <O> sound [did,could] you [hear,listen to]?', # noqa: E501 'What is the number of [sound events,sounds] that have [roughly,approximately] the same duration as the <O> sound have you heard?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question duration = sample_duration() # sample duration lst_events = get_lst_events(narrative) number, ordinal = sample_number(len(lst_events)) question = question.replace('<D>', duration) # insert duration question = question.replace('<O>', ordinal) # insert ordinal question = sanitize_question(question) # correct grammar lst_durations = get_lst_durations(narrative) evt_duration = lst_durations[number - 1] x_durations = [j for i, j in enumerate(lst_durations) if i != (number - 1)] rel_durations_diff = compute_rel_diff(np.array(x_durations), np.array(evt_duration)) # Assert a good margin in relative loudness assert np.sum(np.logical_and(rel_durations_diff > rel_diff, rel_durations_diff < (2 * rel_diff))) <= 0, \ 'Question (how_many_sounds_duration_ordinal) illposed.' answer = numbers_to_words(np.sum(rel_durations_diff <= rel_diff)) return question, answer
def compare_duration_ordinal(dataset, narrative, rel_diff=0.1): questions = [ 'Was the <O1> [sound event,sound] <RD> than the <O2> [sound event,sound]?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O1> [sound event,sound] and the <O2> [sound event,sound], was the former <RD>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O1> and <O2> [sound events,sounds], was the former <RD>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O2> [sound event,sound] and the <O1> [sound event,sound], was the latter <RD>?', # noqa: E501 '[Comparing,Listening to,Hearing] the <O2> and <O1> [sound events,sounds], was the latter <RD>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number_1, ordinal_1 = sample_number(len(lst_events)) rel_duration = sample_rel_duration() number_2, ordinal_2 = sample_second_number(len(lst_events), number_1) assert number_1 != number_2, 'Question (compare_duration_ordinal) illposed.' question = question.replace('<O1>', ordinal_1) # insert ordinal question = question.replace('<RD>', rel_duration) # insert duration question = question.replace('<O2>', ordinal_2) # insert ordinal question = sanitize_question(question) # correct grammar lst_duration = get_lst_durations(narrative) e_1_duration = lst_duration[number_1 - 1] e_2_duration = lst_duration[number_2 - 1] # Assert a good margin in relative duration rel_duration_diff = compute_rel_diff(np.array(e_1_duration), np.array(e_2_duration)) assert np.sum(rel_duration_diff < rel_diff) <= 0, \ 'Question (compare_duration_ordinal) illposed.' if 'short' in question: answer = 'yes' if e_1_duration < e_2_duration else 'no' elif 'long' in question: answer = 'yes' if e_1_duration > e_2_duration else 'no' else: assert False, 'Duration illdefined in Question (compare_duration_ordinal).' return question, answer
def compare_ordinal_event(dataset, narrative, _): questions = [ 'Was the <O> [sound event,sound] [a,an] <S> <A>?', # noqa: E501 'Did the <O> [sound event,sound] [sound,seem] like [a,an] <S> <A>?', # noqa: E501 '[Listening to,Hearing] the <O> [sound event,sound], was it [a,an] <S> <A>?', # noqa: E501 '[Listening to,Hearing] the <O> [sound event,sound], did it [sound,seem] like [a,an] <S> <A>?', # noqa: E501 ] question = str(np.random.choice(questions)) # sample question lst_events = get_lst_events(narrative) number, ordinal = sample_number(len(lst_events)) event = str(np.random.choice(dataset['events'])) # sample event source = str(np.random.choice(dataset['sources'][event])) # sample source action = str(np.random.choice(dataset['actions'][event])) # sample action question = question.replace('<O>', ordinal) # insert ordinal question = question.replace('<S>', source) # insert source question = question.replace('<A>', action) # insert action question = sanitize_question(question) # correct grammar answer = 'yes' if lst_events[number - 1] == event else 'no' return question, answer