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Ensure NLTK resources are loaded on demand #5

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43 changes: 39 additions & 4 deletions core/utils/add_phonemes.py
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Original file line number Diff line number Diff line change
@@ -1,13 +1,46 @@
import json
import logging
import math

import nltk

nltk.download("averaged_perceptron_tagger_eng")

from g2p_en import G2p

g2p = G2p()

logger = logging.getLogger(__name__)

_G2P_MODEL = None
_TAGGER_RESOURCE = "averaged_perceptron_tagger_eng"
_TAGGER_PATH = f"taggers/{_TAGGER_RESOURCE}"


def ensure_nltk_resource(resource_id, resource_path=None):
"""Ensure the given NLTK resource is available, downloading when needed."""

resource_path = resource_path or resource_id
try:
nltk.data.find(resource_path)
except LookupError:
logger.warning(
"Missing NLTK resource '%s'. Attempting download.", resource_id
)
try:
nltk.download(resource_id, quiet=True)
nltk.data.find(resource_path)
except LookupError as exc:
logger.warning(
"Unable to locate NLTK resource '%s' after download attempt: %s",
resource_id,
exc,
)
raise


def get_g2p_model():
global _G2P_MODEL
if _G2P_MODEL is None:
_G2P_MODEL = G2p()
return _G2P_MODEL
# file_name = 'G:/Projects/speech aligner/kamal speech aliner/speach_aliner/app/json/json_data_for_frame/kamal.json'
# with open(file_name, 'r') as f:
# data = json.load(f)
Expand Down Expand Up @@ -50,8 +83,10 @@ def add_phonemes(data, FRAME_PER_SECOUND=24, EXTRA_TIME=0):
print("FRAME_PER_SECOUND:", FRAME_PER_SECOUND)
print("AUDO_END_TIME : ", AUDO_END_TIME)
# print(data['fragments'][0])
ensure_nltk_resource(_TAGGER_RESOURCE, _TAGGER_PATH)
g2p_model = get_g2p_model()
for each_data in data.get("words"):
each_data["phonemes"] = g2p(each_data["word"])
each_data["phonemes"] = g2p_model(each_data["word"])
print(each_data["phonemes"])
each_data["init_frame"] = math.ceil(
float(each_data.get("start", 1)) * FRAME_PER_SECOUND
Expand Down