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Running
on
T4
File size: 2,224 Bytes
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# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import os
import tgt
def get_alignment(tier, cfg):
sample_rate = cfg["sample_rate"]
hop_size = cfg["hop_size"]
sil_phones = ["sil", "sp", "spn"]
phones = []
durations = []
start_time = 0
end_time = 0
end_idx = 0
for t in tier._objects:
s, e, p = t.start_time, t.end_time, t.text
# Trim leading silences
if phones == []:
if p in sil_phones:
continue
else:
start_time = s
if p not in sil_phones:
# For ordinary phones
phones.append(p)
end_time = e
end_idx = len(phones)
else:
# For silent phones
phones.append(p)
durations.append(
int(
np.round(e * sample_rate / hop_size)
- np.round(s * sample_rate / hop_size)
)
)
# Trim tailing silences
phones = phones[:end_idx]
durations = durations[:end_idx]
return phones, durations, start_time, end_time
def get_duration(utt, wav, cfg):
speaker = utt["Singer"]
basename = utt["Uid"]
dataset = utt["Dataset"]
sample_rate = cfg["sample_rate"]
# print(cfg.processed_dir, dataset, speaker, basename)
wav_path = os.path.join(
cfg.processed_dir, dataset, "raw_data", speaker, "{}.wav".format(basename)
)
text_path = os.path.join(
cfg.processed_dir, dataset, "raw_data", speaker, "{}.lab".format(basename)
)
tg_path = os.path.join(
cfg.processed_dir, dataset, "TextGrid", speaker, "{}.TextGrid".format(basename)
)
# Read raw text
with open(text_path, "r") as f:
raw_text = f.readline().strip("\n")
# Get alignments
textgrid = tgt.io.read_textgrid(tg_path)
phone, duration, start, end = get_alignment(
textgrid.get_tier_by_name("phones"), cfg
)
text = "{" + " ".join(phone) + "}"
if start >= end:
return None
return duration, text, int(sample_rate * start), int(sample_rate * end)
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