# 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 os import random import sys import time import warnings 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 ASRWsAudioHandler from paddlespeech.server.utils.audio_process import wav2pcm from paddlespeech.server.utils.util import compute_delay from paddlespeech.server.utils.util import wav2base64 warnings.filterwarnings("ignore") __all__ = [ 'TTSClientExecutor', 'TTSOnlineClientExecutor', 'ASRClientExecutor', 'ASROnlineClientExecutor', 'CLSClientExecutor', 'VectorClientExecutor' ] @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.remove(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.") logger.error(e) 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.tts_online', description='visit tts online service') class TTSOnlineClientExecutor(BaseExecutor): def __init__(self): super(TTSOnlineClientExecutor, self).__init__() self.parser = argparse.ArgumentParser( prog='paddlespeech_client.tts_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=8092, help='server port') self.parser.add_argument( '--protocol', type=str, default="http", choices=["http", "websocket"], help='server protocol') 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') self.parser.add_argument( "--play", type=bool, help="whether to play audio", default=False) def execute(self, argv: List[str]) -> bool: args = self.parser.parse_args(argv) input_ = args.input server_ip = args.server_ip port = args.port protocol = args.protocol spk_id = args.spk_id speed = args.speed volume = args.volume sample_rate = args.sample_rate output = args.output play = args.play try: self( input=input_, server_ip=server_ip, port=port, protocol=protocol, spk_id=spk_id, speed=speed, volume=volume, sample_rate=sample_rate, output=output, play=play) return True except Exception as e: logger.error("Failed to synthesized audio.") logger.error(e) return False @stats_wrapper def __call__(self, input: str, server_ip: str="127.0.0.1", port: int=8092, protocol: str="http", spk_id: int=0, speed: float=1.0, volume: float=1.0, sample_rate: int=0, output: str=None, play: bool=False): """ Python API to call an executor. """ if protocol == "http": logger.info("tts http client start") from paddlespeech.server.utils.audio_handler import TTSHttpHandler handler = TTSHttpHandler(server_ip, port, play) first_response, final_response, duration, save_audio_success, receive_time_list, chunk_duration_list = handler.run( input, spk_id, speed, volume, sample_rate, output) delay_time_list = compute_delay(receive_time_list, chunk_duration_list) elif protocol == "websocket": from paddlespeech.server.utils.audio_handler import TTSWsHandler logger.info("tts websocket client start") handler = TTSWsHandler(server_ip, port, play) loop = asyncio.get_event_loop() first_response, final_response, duration, save_audio_success, receive_time_list, chunk_duration_list = loop.run_until_complete( handler.run(input, output)) delay_time_list = compute_delay(receive_time_list, chunk_duration_list) else: logger.error("Please set correct protocol, http or websocket") sys.exit(-1) logger.info(f"sentence: {input}") logger.info(f"duration: {duration} s") logger.info(f"first response: {first_response} s") logger.info(f"final response: {final_response} s") logger.info(f"RTF: {final_response/duration}") if output is not None: if save_audio_success: logger.info(f"Audio successfully saved in {output}") else: logger.error("Audio save failed.") if delay_time_list != []: logger.info( f"Delay situation: total number of packages: {len(receive_time_list)}, the number of delayed packets: {len(delay_time_list)}, minimum delay time: {min(delay_time_list)} s, maximum delay time: {max(delay_time_list)} s, average delay time: {sum(delay_time_list)/len(delay_time_list)} s, delay rate:{len(delay_time_list)/len(receive_time_list)}" ) else: logger.info("The sentence has no delay in streaming synthesis.") @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( '--protocol', type=str, default="http", choices=["http", "websocket"], help='server protocol') 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') self.parser.add_argument( '--punc.server_ip', type=str, default=None, dest="punc_server_ip", help='Punctuation server ip') self.parser.add_argument( '--punc.port', type=int, default=8091, dest="punc_server_port", help='Punctuation server port') 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 protocol = args.protocol 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, protocol=protocol, punc_server_ip=args.punc_server_ip, punc_server_port=args.punc_server_port) time_end = time.time() logger.info(f"ASR result: {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=8090, sample_rate: int=16000, lang: str="zh_cn", audio_format: str="wav", protocol: str="http", punc_server_ip: str=None, punc_server_port: int=None): """Python API to call an executor. Args: input (str): The input audio file path server_ip (str, optional): The ASR server ip. Defaults to "127.0.0.1". port (int, optional): The ASR server port. Defaults to 8090. sample_rate (int, optional): The audio sample rate. Defaults to 16000. lang (str, optional): The audio language type. Defaults to "zh_cn". audio_format (str, optional): The audio format information. Defaults to "wav". protocol (str, optional): The ASR server. Defaults to "http". Returns: str: The ASR results """ # we use the asr server to recognize the audio text content # and paddlespeech_client asr only support http protocol protocol = "http" if protocol.lower() == "http": from paddlespeech.server.utils.audio_handler import ASRHttpHandler logger.info("asr http client start") handler = ASRHttpHandler(server_ip=server_ip, port=port) res = handler.run(input, audio_format, sample_rate, lang) res = res['result']['transcription'] logger.info("asr http client finished") else: logger.error(f"Sorry, we have not support protocol: {protocol}," "please use http or websocket protocol") sys.exit(-1) 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') self.parser.add_argument( '--punc.server_ip', type=str, default=None, dest="punc_server_ip", help='Punctuation server ip') self.parser.add_argument( '--punc.port', type=int, default=8190, dest="punc_server_port", help='Punctuation server port') 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, punc_server_ip=args.punc_server_ip, punc_server_port=args.punc_server_port) 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", punc_server_ip: str=None, punc_server_port: str=None): """Python API to call asr online executor. Args: input (str): the audio file to be send to streaming asr service. server_ip (str, optional): streaming asr server ip. Defaults to "127.0.0.1". port (int, optional): streaming asr server port. Defaults to 8091. sample_rate (int, optional): audio sample rate. Defaults to 16000. lang (str, optional): audio language type. Defaults to "zh_cn". audio_format (str, optional): audio format. Defaults to "wav". punc_server_ip (str, optional): punctuation server ip. Defaults to None. punc_server_port (str, optional): punctuation server port. Defaults to None. Returns: str: the audio text """ logger.info("asr websocket client start") handler = ASRWsAudioHandler( server_ip, port, punc_server_ip=punc_server_ip, punc_server_port=punc_server_port) loop = asyncio.get_event_loop() res = loop.run_until_complete(handler.run(input)) logger.info("asr websocket client finished") return res['result'] @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.") logger.error(e) 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 @cli_client_register( name='paddlespeech_client.text', description='visit the text service') class TextClientExecutor(BaseExecutor): def __init__(self): super(TextClientExecutor, self).__init__() self.parser = argparse.ArgumentParser( prog='paddlespeech_client.text', 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='sentence to be process by text server.', required=True) def execute(self, argv: List[str]) -> bool: """Execute the request from the argv. Args: argv (List): the request arguments Returns: str: the request flag """ args = self.parser.parse_args(argv) input_ = args.input server_ip = args.server_ip port = args.port try: time_start = time.time() res = self(input=input_, server_ip=server_ip, port=port) time_end = time.time() logger.info(f"The punc text: {res}") logger.info("Response time %f s." % (time_end - time_start)) return True except Exception as e: logger.error("Failed to Text punctuation.") return False @stats_wrapper def __call__(self, input: str, server_ip: str="127.0.0.1", port: int=8090): """ Python API to call text executor. Args: input (str): the request sentence text server_ip (str, optional): the server ip. Defaults to "127.0.0.1". port (int, optional): the server port. Defaults to 8090. Returns: str: the punctuation text """ url = 'http://' + server_ip + ":" + str(port) + '/paddlespeech/text' request = { "text": input, } res = requests.post(url=url, data=json.dumps(request)) response_dict = res.json() punc_text = response_dict["result"]["punc_text"] return punc_text @cli_client_register( name='paddlespeech_client.vector', description='visit the vector service') class VectorClientExecutor(BaseExecutor): def __init__(self): super(VectorClientExecutor, self).__init__() self.parser = argparse.ArgumentParser( prog='paddlespeech_client.vector', 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='sentence to be process by text server.') self.parser.add_argument( '--task', type=str, default="spk", choices=["spk", "score"], help="The vector service task") self.parser.add_argument( "--enroll", type=str, default=None, help="The enroll audio") self.parser.add_argument( "--test", type=str, default=None, help="The test audio") def execute(self, argv: List[str]) -> bool: """Execute the request from the argv. Args: argv (List): the request arguments Returns: str: the request flag """ args = self.parser.parse_args(argv) input_ = args.input server_ip = args.server_ip port = args.port task = args.task try: time_start = time.time() res = self( input=input_, server_ip=server_ip, port=port, enroll_audio=args.enroll, test_audio=args.test, task=task) time_end = time.time() logger.info(f"The vector: {res}") logger.info("Response time %f s." % (time_end - time_start)) return True except Exception as e: logger.error("Failed to extract vector.") logger.error(e) return False @stats_wrapper def __call__(self, input: str, server_ip: str="127.0.0.1", port: int=8090, audio_format: str="wav", sample_rate: int=16000, enroll_audio: str=None, test_audio: str=None, task="spk"): """ Python API to call text executor. Args: input (str): the request audio data server_ip (str, optional): the server ip. Defaults to "127.0.0.1". port (int, optional): the server port. Defaults to 8090. audio_format (str, optional): audio format. Defaults to "wav". sample_rate (str, optional): audio sample rate. Defaults to 16000. enroll_audio (str, optional): enroll audio data. Defaults to None. test_audio (str, optional): test audio data. Defaults to None. task (str, optional): the task type, "spk" or "socre". Defaults to "spk" Returns: str: the audio embedding or score between enroll and test audio """ if task == "spk": from paddlespeech.server.utils.audio_handler import VectorHttpHandler logger.info("vector http client start") logger.info(f"the input audio: {input}") handler = VectorHttpHandler(server_ip=server_ip, port=port) res = handler.run(input, audio_format, sample_rate) return res elif task == "score": from paddlespeech.server.utils.audio_handler import VectorScoreHttpHandler logger.info("vector score http client start") logger.info( f"enroll audio: {enroll_audio}, test audio: {test_audio}") handler = VectorScoreHttpHandler(server_ip=server_ip, port=port) res = handler.run(enroll_audio, test_audio, audio_format, sample_rate) logger.info(f"The vector score is: {res}") return res else: logger.error(f"Sorry, we have not support such task {task}") @cli_client_register( name='paddlespeech_client.acs', description='visit acs service') class ACSClientExecutor(BaseExecutor): def __init__(self): super(ACSClientExecutor, self).__init__() self.parser = argparse.ArgumentParser( prog='paddlespeech_client.acs', 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(f"ACS result: {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=8090, sample_rate: int=16000, lang: str="zh_cn", audio_format: str="wav", ): """Python API to call an executor. Args: input (str): The input audio file path server_ip (str, optional): The ASR server ip. Defaults to "127.0.0.1". port (int, optional): The ASR server port. Defaults to 8090. sample_rate (int, optional): The audio sample rate. Defaults to 16000. lang (str, optional): The audio language type. Defaults to "zh_cn". audio_format (str, optional): The audio format information. Defaults to "wav". Returns: str: The ACS results """ # we use the acs server to get the key word time stamp in audio text content logger.info("acs http client start") from paddlespeech.server.utils.audio_handler import ASRHttpHandler handler = ASRHttpHandler( server_ip=server_ip, port=port, endpoint="/paddlespeech/asr/search") res = handler.run(input, audio_format, sample_rate, lang) res = res['result'] logger.info("acs http client finished") return res