src/preprocess/MInDS-14.py

import os

# import pandas as pd
from utils import read_csv_file, write_jsonl_file, parse

# new read_in function
# def read_csv_file(filename):
#     with open(filename, "r", encoding="utf8") as fr:
#         return pd.read_csv(fr)


def preprocess(args):
    filenames = os.listdir(args.input_dir)
    for filename in filenames:
        """
        add train/eval/test instruction
        """

        if not filename.endswith(".csv"):
            continue

        path = os.path.join(args.input_dir, filename)
        data = read_csv_file(path)
        turns = []
        locale = filename[:5] if filename != "aux-en.csv" else "en-US"

        for i in data.index:
            t = {"turn": "single", "locale": locale, "dialog": []}
            item = data.iloc[i]
            d = {
                "role": "ROLE",
                "utterance": item["text_asr"] if filename != "aux-en.csv" else item[0],
                "active_intents": [
                    item["intent"] if filename != "aux-en.csv" else item[1]
                ],
            }
            t["dialog"].append(d)
            turns.append(t)

            if locale != "en-US":
                t_en = {"turn": "single", "locale": "en-US", "dialog": []}
                d = {
                    "role": "ROLE",
                    "utterance": item["text_translated"],
                    "active_intents": [item["intent"]],
                }
                t_en["dialog"].append(d)
                turns.append(t_en)

        write_jsonl_file(turns, args.output_dir + "/" + filename[:5] + ".jsonl")


if __name__ == "__main__":
    args = parse()
    preprocess(args)