# 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 asyncio import base64 import io import json import logging import os import random import time from typing import List 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_handler import ASRAudioHandler from paddlespeech.server.utils.audio_process import wav2pcm from paddlespeech.server.utils.util import wav2base64 __all__ = [ 'TTSClientExecutor', 'ASRClientExecutor', 'ASROnlineClientExecutor', '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 ASROnlineClientExecutor(BaseExecutor): def __init__(self): super(ASROnlineClientExecutor, self).__init__() self.parser = argparse.ArgumentParser( prog='paddlespeech_client.asr_online', 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) logger.info("Response time %f s." % (time_end - time_start)) return True except Exception as e: logger.error("Failed to speech recognition.") logger.error(e) 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() res = loop.run_until_complete(handler.run(input)) logging.info("asr websocket client finished") return res['asr_results'] @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