You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
362 lines
12 KiB
362 lines
12 KiB
# Copyright (c) 2021 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 specific language governing permissions and
|
|
# limitations under the License.
|
|
import argparse
|
|
import base64
|
|
import io
|
|
import json
|
|
import os
|
|
import random
|
|
import time
|
|
from typing import List
|
|
import logging
|
|
import asyncio
|
|
|
|
import numpy as np
|
|
import requests
|
|
import soundfile
|
|
|
|
from ..executor import BaseExecutor
|
|
from ..util import cli_client_register
|
|
from ..util import stats_wrapper
|
|
from paddlespeech.cli.log import logger
|
|
from paddlespeech.server.utils.audio_process import wav2pcm
|
|
from paddlespeech.server.utils.util import wav2base64
|
|
from paddlespeech.server.tests.asr.online.websocket_client import ASRAudioHandler
|
|
|
|
__all__ = ['TTSClientExecutor', 'ASRClientExecutor', 'CLSClientExecutor']
|
|
|
|
|
|
@cli_client_register(
|
|
name='paddlespeech_client.tts', description='visit tts service')
|
|
class TTSClientExecutor(BaseExecutor):
|
|
def __init__(self):
|
|
super(TTSClientExecutor, self).__init__()
|
|
self.parser = argparse.ArgumentParser(
|
|
prog='paddlespeech_client.tts', add_help=True)
|
|
self.parser.add_argument(
|
|
'--server_ip', type=str, default='127.0.0.1', help='server ip')
|
|
self.parser.add_argument(
|
|
'--port', type=int, default=8090, help='server port')
|
|
self.parser.add_argument(
|
|
'--input',
|
|
type=str,
|
|
default=None,
|
|
help='Text to be synthesized.',
|
|
required=True)
|
|
self.parser.add_argument(
|
|
'--spk_id', type=int, default=0, help='Speaker id')
|
|
self.parser.add_argument(
|
|
'--speed',
|
|
type=float,
|
|
default=1.0,
|
|
help='Audio speed, the value should be set between 0 and 3')
|
|
self.parser.add_argument(
|
|
'--volume',
|
|
type=float,
|
|
default=1.0,
|
|
help='Audio volume, the value should be set between 0 and 3')
|
|
self.parser.add_argument(
|
|
'--sample_rate',
|
|
type=int,
|
|
default=0,
|
|
choices=[0, 8000, 16000],
|
|
help='Sampling rate, the default is the same as the model')
|
|
self.parser.add_argument(
|
|
'--output', type=str, default=None, help='Synthesized audio file')
|
|
|
|
def postprocess(self, wav_base64: str, outfile: str) -> float:
|
|
audio_data_byte = base64.b64decode(wav_base64)
|
|
# from byte
|
|
samples, sample_rate = soundfile.read(
|
|
io.BytesIO(audio_data_byte), dtype='float32')
|
|
|
|
# transform audio
|
|
if outfile.endswith(".wav"):
|
|
soundfile.write(outfile, samples, sample_rate)
|
|
elif outfile.endswith(".pcm"):
|
|
temp_wav = str(random.getrandbits(128)) + ".wav"
|
|
soundfile.write(temp_wav, samples, sample_rate)
|
|
wav2pcm(temp_wav, outfile, data_type=np.int16)
|
|
os.system("rm %s" % (temp_wav))
|
|
else:
|
|
logger.error("The format for saving audio only supports wav or pcm")
|
|
|
|
def execute(self, argv: List[str]) -> bool:
|
|
args = self.parser.parse_args(argv)
|
|
input_ = args.input
|
|
server_ip = args.server_ip
|
|
port = args.port
|
|
spk_id = args.spk_id
|
|
speed = args.speed
|
|
volume = args.volume
|
|
sample_rate = args.sample_rate
|
|
output = args.output
|
|
|
|
try:
|
|
time_start = time.time()
|
|
res = self(
|
|
input=input_,
|
|
server_ip=server_ip,
|
|
port=port,
|
|
spk_id=spk_id,
|
|
speed=speed,
|
|
volume=volume,
|
|
sample_rate=sample_rate,
|
|
output=output)
|
|
time_end = time.time()
|
|
time_consume = time_end - time_start
|
|
response_dict = res.json()
|
|
logger.info(response_dict["message"])
|
|
logger.info("Save synthesized audio successfully on %s." % (output))
|
|
logger.info("Audio duration: %f s." %
|
|
(response_dict['result']['duration']))
|
|
logger.info("Response time: %f s." % (time_consume))
|
|
return True
|
|
except Exception as e:
|
|
logger.error("Failed to synthesized audio.")
|
|
return False
|
|
|
|
@stats_wrapper
|
|
def __call__(self,
|
|
input: str,
|
|
server_ip: str="127.0.0.1",
|
|
port: int=8090,
|
|
spk_id: int=0,
|
|
speed: float=1.0,
|
|
volume: float=1.0,
|
|
sample_rate: int=0,
|
|
output: str=None):
|
|
"""
|
|
Python API to call an executor.
|
|
"""
|
|
|
|
url = 'http://' + server_ip + ":" + str(port) + '/paddlespeech/tts'
|
|
request = {
|
|
"text": input,
|
|
"spk_id": spk_id,
|
|
"speed": speed,
|
|
"volume": volume,
|
|
"sample_rate": sample_rate,
|
|
"save_path": output
|
|
}
|
|
|
|
res = requests.post(url, json.dumps(request))
|
|
response_dict = res.json()
|
|
if output is not None:
|
|
self.postprocess(response_dict["result"]["audio"], output)
|
|
return res
|
|
|
|
|
|
@cli_client_register(
|
|
name='paddlespeech_client.asr', description='visit asr service')
|
|
class ASRClientExecutor(BaseExecutor):
|
|
def __init__(self):
|
|
super(ASRClientExecutor, self).__init__()
|
|
self.parser = argparse.ArgumentParser(
|
|
prog='paddlespeech_client.asr', add_help=True)
|
|
self.parser.add_argument(
|
|
'--server_ip', type=str, default='127.0.0.1', help='server ip')
|
|
self.parser.add_argument(
|
|
'--port', type=int, default=8090, help='server port')
|
|
self.parser.add_argument(
|
|
'--input',
|
|
type=str,
|
|
default=None,
|
|
help='Audio file to be recognized',
|
|
required=True)
|
|
self.parser.add_argument(
|
|
'--sample_rate', type=int, default=16000, help='audio sample rate')
|
|
self.parser.add_argument(
|
|
'--lang', type=str, default="zh_cn", help='language')
|
|
self.parser.add_argument(
|
|
'--audio_format', type=str, default="wav", help='audio format')
|
|
|
|
def execute(self, argv: List[str]) -> bool:
|
|
args = self.parser.parse_args(argv)
|
|
input_ = args.input
|
|
server_ip = args.server_ip
|
|
port = args.port
|
|
sample_rate = args.sample_rate
|
|
lang = args.lang
|
|
audio_format = args.audio_format
|
|
|
|
try:
|
|
time_start = time.time()
|
|
res = self(
|
|
input=input_,
|
|
server_ip=server_ip,
|
|
port=port,
|
|
sample_rate=sample_rate,
|
|
lang=lang,
|
|
audio_format=audio_format)
|
|
time_end = time.time()
|
|
logger.info(res.json())
|
|
logger.info("Response time %f s." % (time_end - time_start))
|
|
return True
|
|
except Exception as e:
|
|
logger.error("Failed to speech recognition.")
|
|
return False
|
|
|
|
@stats_wrapper
|
|
def __call__(self,
|
|
input: str,
|
|
server_ip: str="127.0.0.1",
|
|
port: int=8090,
|
|
sample_rate: int=16000,
|
|
lang: str="zh_cn",
|
|
audio_format: str="wav"):
|
|
"""
|
|
Python API to call an executor.
|
|
"""
|
|
|
|
url = 'http://' + server_ip + ":" + str(port) + '/paddlespeech/asr'
|
|
audio = wav2base64(input)
|
|
data = {
|
|
"audio": audio,
|
|
"audio_format": audio_format,
|
|
"sample_rate": sample_rate,
|
|
"lang": lang,
|
|
}
|
|
|
|
res = requests.post(url=url, data=json.dumps(data))
|
|
return res
|
|
|
|
|
|
@cli_client_register(
|
|
name='paddlespeech_client.asr_online', description='visit asr online service')
|
|
class ASRClientExecutor(BaseExecutor):
|
|
def __init__(self):
|
|
super(ASRClientExecutor, self).__init__()
|
|
self.parser = argparse.ArgumentParser(
|
|
prog='paddlespeech_client.asr', add_help=True)
|
|
self.parser.add_argument(
|
|
'--server_ip', type=str, default='127.0.0.1', help='server ip')
|
|
self.parser.add_argument(
|
|
'--port', type=int, default=8091, help='server port')
|
|
self.parser.add_argument(
|
|
'--input',
|
|
type=str,
|
|
default=None,
|
|
help='Audio file to be recognized',
|
|
required=True)
|
|
self.parser.add_argument(
|
|
'--sample_rate', type=int, default=16000, help='audio sample rate')
|
|
self.parser.add_argument(
|
|
'--lang', type=str, default="zh_cn", help='language')
|
|
self.parser.add_argument(
|
|
'--audio_format', type=str, default="wav", help='audio format')
|
|
|
|
def execute(self, argv: List[str]) -> bool:
|
|
args = self.parser.parse_args(argv)
|
|
input_ = args.input
|
|
server_ip = args.server_ip
|
|
port = args.port
|
|
sample_rate = args.sample_rate
|
|
lang = args.lang
|
|
audio_format = args.audio_format
|
|
|
|
try:
|
|
time_start = time.time()
|
|
res = self(
|
|
input=input_,
|
|
server_ip=server_ip,
|
|
port=port,
|
|
sample_rate=sample_rate,
|
|
lang=lang,
|
|
audio_format=audio_format)
|
|
time_end = time.time()
|
|
logger.info(res.json())
|
|
logger.info("Response time %f s." % (time_end - time_start))
|
|
return True
|
|
except Exception as e:
|
|
logger.error("Failed to speech recognition.")
|
|
return False
|
|
|
|
@stats_wrapper
|
|
def __call__(self,
|
|
input: str,
|
|
server_ip: str="127.0.0.1",
|
|
port: int=8091,
|
|
sample_rate: int=16000,
|
|
lang: str="zh_cn",
|
|
audio_format: str="wav"):
|
|
"""
|
|
Python API to call an executor.
|
|
"""
|
|
logging.basicConfig(level=logging.INFO)
|
|
logging.info("asr websocket client start")
|
|
handler = ASRAudioHandler(server_ip, port)
|
|
loop = asyncio.get_event_loop()
|
|
loop.run_until_complete(handler.run(input))
|
|
logging.info("asr websocket client finished")
|
|
|
|
|
|
@cli_client_register(
|
|
name='paddlespeech_client.cls', description='visit cls service')
|
|
class CLSClientExecutor(BaseExecutor):
|
|
def __init__(self):
|
|
super(CLSClientExecutor, self).__init__()
|
|
self.parser = argparse.ArgumentParser(
|
|
prog='paddlespeech_client.cls', add_help=True)
|
|
self.parser.add_argument(
|
|
'--server_ip', type=str, default='127.0.0.1', help='server ip')
|
|
self.parser.add_argument(
|
|
'--port', type=int, default=8090, help='server port')
|
|
self.parser.add_argument(
|
|
'--input',
|
|
type=str,
|
|
default=None,
|
|
help='Audio file to classify.',
|
|
required=True)
|
|
self.parser.add_argument(
|
|
'--topk',
|
|
type=int,
|
|
default=1,
|
|
help='Return topk scores of classification result.')
|
|
|
|
def execute(self, argv: List[str]) -> bool:
|
|
args = self.parser.parse_args(argv)
|
|
input_ = args.input
|
|
server_ip = args.server_ip
|
|
port = args.port
|
|
topk = args.topk
|
|
|
|
try:
|
|
time_start = time.time()
|
|
res = self(input=input_, server_ip=server_ip, port=port, topk=topk)
|
|
time_end = time.time()
|
|
logger.info(res.json())
|
|
logger.info("Response time %f s." % (time_end - time_start))
|
|
return True
|
|
except Exception as e:
|
|
logger.error("Failed to speech classification.")
|
|
return False
|
|
|
|
@stats_wrapper
|
|
def __call__(self,
|
|
input: str,
|
|
server_ip: str="127.0.0.1",
|
|
port: int=8090,
|
|
topk: int=1):
|
|
"""
|
|
Python API to call an executor.
|
|
"""
|
|
|
|
url = 'http://' + server_ip + ":" + str(port) + '/paddlespeech/cls'
|
|
audio = wav2base64(input)
|
|
data = {"audio": audio, "topk": topk}
|
|
|
|
res = requests.post(url=url, data=json.dumps(data))
|
|
return res
|