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PaddleSpeech/paddlespeech/server/utils/util.py

78 lines
2.0 KiB

# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the
import base64
import math
def wav2base64(wav_file: str):
"""
read wave file and covert to base64 string
"""
with open(wav_file, 'rb') as f:
base64_bytes = base64.b64encode(f.read())
base64_string = base64_bytes.decode('utf-8')
return base64_string
def base64towav(base64_string: str):
pass
def self_check():
""" self check resource
"""
return True
def denorm(data, mean, std):
"""stream am model need to denorm
"""
return data * std + mean
def get_chunks(data, block_size, pad_size, step):
"""Divide data into multiple chunks
Args:
data (tensor): data
block_size (int): [description]
pad_size (int): [description]
step (str): set "am" or "voc", generate chunk for step am or vocoder(voc)
Returns:
list: chunks list
"""
if block_size == -1:
return [data]
if step == "am":
data_len = data.shape[1]
elif step == "voc":
data_len = data.shape[0]
else:
print("Please set correct type to get chunks, am or voc")
chunks = []
n = math.ceil(data_len / block_size)
for i in range(n):
start = max(0, i * block_size - pad_size)
end = min((i + 1) * block_size + pad_size, data_len)
if step == "am":
chunks.append(data[:, start:end, :])
elif step == "voc":
chunks.append(data[start:end, :])
else:
print("Please set correct type to get chunks, am or voc")
return chunks