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105 lines
3.3 KiB
105 lines
3.3 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import base64
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import io
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import json
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import os
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import random
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import time
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import numpy as np
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import requests
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import soundfile
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from paddlespeech.server.utils.audio_process import wav2pcm
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# Request and response
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def tts_client(args):
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""" Request and response
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Args:
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text: A sentence to be synthesized
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outfile: Synthetic audio file
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"""
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url = 'http://127.0.0.1:8090/paddlespeech/tts'
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request = {
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"text": args.text,
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"spk_id": args.spk_id,
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"speed": args.speed,
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"volume": args.volume,
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"sample_rate": args.sample_rate,
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"save_path": args.output
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}
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response = requests.post(url, json.dumps(request))
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response_dict = response.json()
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wav_base64 = response_dict["result"]["audio"]
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audio_data_byte = base64.b64decode(wav_base64)
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# from byte
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samples, sample_rate = soundfile.read(
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io.BytesIO(audio_data_byte), dtype='float32')
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# transform audio
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outfile = args.output
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if outfile.endswith(".wav"):
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soundfile.write(outfile, samples, sample_rate)
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elif outfile.endswith(".pcm"):
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temp_wav = str(random.getrandbits(128)) + ".wav"
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soundfile.write(temp_wav, samples, sample_rate)
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wav2pcm(temp_wav, outfile, data_type=np.int16)
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os.system("rm %s" % (temp_wav))
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else:
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print("The format for saving audio only supports wav or pcm")
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return len(samples), sample_rate
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'--text',
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type=str,
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default="你好，欢迎使用语音合成服务",
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help='A sentence to be synthesized')
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parser.add_argument('--spk_id', type=int, default=0, help='Speaker id')
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parser.add_argument('--speed', type=float, default=1.0, help='Audio speed')
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parser.add_argument(
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'--volume', type=float, default=1.0, help='Audio volume')
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parser.add_argument(
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'--sample_rate',
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type=int,
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default=0,
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help='Sampling rate, the default is the same as the model')
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parser.add_argument(
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'--output',
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type=str,
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default="./out.wav",
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help='Synthesized audio file')
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args = parser.parse_args()
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st = time.time()
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try:
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samples_length, sample_rate = tts_client(args)
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time_consume = time.time() - st
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duration = samples_length / sample_rate
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rtf = time_consume / duration
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print("Synthesized audio successfully.")
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print("Inference time: %f" % (time_consume))
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print("The duration of synthesized audio: %f" % (duration))
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print("The RTF is: %f" % (rtf))
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except BaseException:
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print("Failed to synthesized audio.")
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