---
license: apache-2.0
---

Data checkpoints from https://github.com/hexgrad/misaki for Grapheme To Phoneme (G2P) conversion.


## Code to generate:
```py
!git clone https://github.com/hexgrad/misaki
%cd misaki

import subprocess
import json
import pandas as pd
from misaki import __version__

def get_git_commit_hash():
  result = subprocess.run(["git", "rev-parse", "HEAD"], capture_output=True, text=True, check=True)
  return result.stdout.strip()

def get_rows(data, language):
  rows = []
  for key, values in data.items():
    if not isinstance(values, dict):
      values = dict(DEFAULT=values)
    for pos, phonemes in values.items():
      rows.append(dict(
        language=language,
        word=key,
        pos=pos,
        phonemes=phonemes,
      ))
  return rows

dictionaries = ["us_gold", "us_silver", "gb_gold", "gb_silver"]
data = {}
for dictionary in dictionaries:
  with open(f"./misaki/data/{dictionary}.json") as f:
    data[dictionary] = json.load(f)

rows = []
for dictionary, data in data.items():
  rows.extend(get_rows(data, f"en-{'US' if dictionary.startswith('us_') else 'GB'}"))

df = pd.DataFrame(rows)
commit_hash = get_git_commit_hash()
dataset_name = f"{__version__}-{commit_hash}.parquet"
df.to_parquet(dataset_name)
```