| import copy |
| import json |
| import os |
| from zipfile import ZipFile, ZIP_DEFLATED |
| from shutil import rmtree |
|
|
| ontology = { |
| 'domains': { |
| 'restaurant': { |
| 'description': 'search for a restaurant to dine', |
| 'slots': { |
| 'food': { |
| 'description': 'food type of the restaurant', |
| 'is_categorical': False, |
| 'possible_values': [] |
| }, |
| 'area': { |
| 'description': 'area of the restaurant', |
| 'is_categorical': True, |
| 'possible_values': ["east", "west", "centre", "north", "south"] |
| }, |
| 'postcode': { |
| 'description': 'postal code of the restaurant', |
| 'is_categorical': False, |
| 'possible_values': [] |
| }, |
| 'phone': { |
| 'description': 'phone number of the restaurant', |
| 'is_categorical': False, |
| 'possible_values': [] |
| }, |
| 'address': { |
| 'description': 'address of the restaurant', |
| 'is_categorical': False, |
| 'possible_values': [] |
| }, |
| 'price range': { |
| 'description': 'price range of the restaurant', |
| 'is_categorical': True, |
| 'possible_values': ["expensive", "moderate", "cheap"] |
| }, |
| 'name': { |
| 'description': 'name of the restaurant', |
| 'is_categorical': False, |
| 'possible_values': [] |
| } |
| } |
| } |
| }, |
| 'intents': { |
| 'inform': { |
| 'description': 'system informs user the value of a slot' |
| }, |
| 'request': { |
| 'description': 'system asks the user to provide value of a slot' |
| } |
| }, |
| 'state': { |
| 'restaurant': { |
| 'food': '', |
| 'area': '', |
| 'postcode': '', |
| 'phone': '', |
| 'address': '', |
| 'price range': '', |
| 'name': '' |
| } |
| }, |
| "dialogue_acts": { |
| "categorical": {}, |
| "non-categorical": {}, |
| "binary": {} |
| } |
| } |
|
|
|
|
| def convert_da(da, utt): |
| global ontology |
|
|
| converted = { |
| 'binary': [], |
| 'categorical': [], |
| 'non-categorical': [] |
| } |
|
|
| for s, v in da: |
| if s == 'request': |
| converted['binary'].append({ |
| 'intent': 'request', |
| 'domain': 'restaurant', |
| 'slot': v, |
| }) |
|
|
| else: |
| slot_type = 'categorical' if ontology['domains']['restaurant']['slots'][s]['is_categorical'] else 'non-categorical' |
|
|
| v = v.strip() |
| if v != 'dontcare' and ontology['domains']['restaurant']['slots'][s]['is_categorical']: |
| if v == 'center': |
| v = 'centre' |
| elif v == 'east side': |
| v = 'east' |
| assert v in ontology['domains']['restaurant']['slots'][s]['possible_values'], print([s,v, utt]) |
|
|
| converted[slot_type].append({ |
| 'intent': 'inform', |
| 'domain': 'restaurant', |
| 'slot': s, |
| 'value': v |
| }) |
|
|
| if slot_type == 'non-categorical' and v != 'dontcare': |
|
|
| start = utt.lower().find(v) |
|
|
| if start != -1: |
| end = start + len(v) |
| converted[slot_type][-1]['start'] = start |
| converted[slot_type][-1]['end'] = end |
| converted[slot_type][-1]['value'] = utt[start:end] |
|
|
| return converted |
|
|
|
|
| def preprocess(): |
| original_data_dir = 'woz' |
| new_data_dir = 'data' |
| os.makedirs(new_data_dir, exist_ok=True) |
|
|
| dataset = 'woz' |
| splits = ['train', 'validation', 'test'] |
| domain = 'restaurant' |
| dialogues_by_split = {split: [] for split in splits} |
| global ontology |
| |
| for split in splits: |
| if split != 'validation': |
| filename = os.path.join(original_data_dir, f'woz_{split}_en.json') |
| else: |
| filename = os.path.join(original_data_dir, 'woz_validate_en.json') |
| if not os.path.exists(filename): |
| raise FileNotFoundError( |
| f'cannot find {filename}, should manually download from https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz') |
|
|
| data = json.load(open(filename)) |
|
|
| for item in data: |
| dialogue = { |
| 'dataset': dataset, |
| 'data_split': split, |
| 'dialogue_id': f'{dataset}-{split}-{len(dialogues_by_split[split])}', |
| 'original_id': item['dialogue_idx'], |
| 'domains': [domain], |
| 'turns': [] |
| } |
|
|
| turns = item['dialogue'] |
| n_turn = len(turns) |
|
|
| for i in range(n_turn): |
| sys_utt = turns[i]['system_transcript'].strip() |
| usr_utt = turns[i]['transcript'].strip() |
| usr_da = turns[i]['turn_label'] |
|
|
| for s, v in usr_da: |
| if s == 'request': |
| assert v in ontology['domains']['restaurant']['slots'] |
| else: |
| assert s in ontology['domains']['restaurant']['slots'] |
|
|
| if i != 0: |
| dialogue['turns'].append({ |
| 'utt_idx': len(dialogue['turns']), |
| 'speaker': 'system', |
| 'utterance': sys_utt, |
| }) |
|
|
| cur_state = copy.deepcopy(ontology['state']) |
| for act_slots in turns[i]['belief_state']: |
| act, slots = act_slots['act'], act_slots['slots'] |
| if act == 'inform': |
| for s, v in slots: |
| v = v.strip() |
| if v != 'dontcare' and ontology['domains']['restaurant']['slots'][s]['is_categorical']: |
| if v not in ontology['domains']['restaurant']['slots'][s]['possible_values']: |
| if v == 'center': |
| v = 'centre' |
| elif v == 'east side': |
| v = 'east' |
| assert v in ontology['domains']['restaurant']['slots'][s]['possible_values'] |
| |
| cur_state[domain][s] = v |
|
|
| cur_usr_da = convert_da(usr_da, usr_utt) |
|
|
| |
| for da_type in cur_usr_da: |
| das = cur_usr_da[da_type] |
| for da in das: |
| ontology["dialogue_acts"][da_type].setdefault((da['intent'], da['domain'], da['slot']), {}) |
| ontology["dialogue_acts"][da_type][(da['intent'], da['domain'], da['slot'])]['user'] = True |
|
|
| dialogue['turns'].append({ |
| 'utt_idx': len(dialogue['turns']), |
| 'speaker': 'user', |
| 'utterance': usr_utt, |
| 'state': cur_state, |
| 'dialogue_acts': cur_usr_da, |
| }) |
|
|
| dialogues_by_split[split].append(dialogue) |
|
|
| dialogues = [] |
| for split in splits: |
| dialogues += dialogues_by_split[split] |
| for da_type in ontology['dialogue_acts']: |
| ontology["dialogue_acts"][da_type] = sorted([str( |
| {'user': speakers.get('user', False), 'system': speakers.get('system', False), 'intent': da[0], |
| 'domain': da[1], 'slot': da[2]}) for da, speakers in ontology["dialogue_acts"][da_type].items()]) |
| json.dump(dialogues[:10], open(f'dummy_data.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) |
| json.dump(ontology, open(f'{new_data_dir}/ontology.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) |
| json.dump(dialogues, open(f'{new_data_dir}/dialogues.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) |
| with ZipFile('data.zip', 'w', ZIP_DEFLATED) as zf: |
| for filename in os.listdir(new_data_dir): |
| zf.write(f'{new_data_dir}/{filename}') |
| rmtree(original_data_dir) |
| rmtree(new_data_dir) |
| return dialogues, ontology |
|
|
|
|
| if __name__ == '__main__': |
| preprocess() |
|
|
