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227 lines
7.4 KiB
227 lines
7.4 KiB
# Copyright (c) 2022 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 io
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import json
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import os
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import re
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import numpy as np
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import paddle
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import soundfile
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import websocket
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from paddlespeech.cli.log import logger
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from paddlespeech.server.engine.base_engine import BaseEngine
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class ACSEngine(BaseEngine):
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def __init__(self):
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"""The ACSEngine Engine
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"""
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super(ACSEngine, self).__init__()
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logger.debug("Create the ACSEngine Instance")
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self.word_list = []
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def init(self, config: dict):
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"""Init the ACSEngine Engine
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Args:
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config (dict): The server configuation
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Returns:
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bool: The engine instance flag
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"""
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logger.debug("Init the acs engine")
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try:
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self.config = config
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self.device = self.config.get("device", paddle.get_device())
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# websocket default ping timeout is 20 seconds
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self.ping_timeout = self.config.get("ping_timeout", 20)
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paddle.set_device(self.device)
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logger.debug(f"ACS Engine set the device: {self.device}")
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except BaseException as e:
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logger.error(
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"Set device failed, please check if device is already used and the parameter 'device' in the yaml file"
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)
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logger.error("Initialize Text server engine Failed on device: %s." %
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(self.device))
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return False
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self.read_search_words()
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# init the asr url
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self.url = "ws://" + self.config.asr_server_ip + ":" + str(
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self.config.asr_server_port) + "/paddlespeech/asr/streaming"
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logger.info("Initialize acs server engine successfully on device: %s." %
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(self.device))
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return True
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def read_search_words(self):
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word_list = self.config.word_list
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if word_list is None:
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logger.error(
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"No word list file in config, please set the word list parameter"
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)
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return
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if not os.path.exists(word_list):
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logger.error("Please input correct word list file")
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return
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with open(word_list, 'r') as fp:
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self.word_list = [line.strip() for line in fp.readlines()]
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logger.info(f"word list: {self.word_list}")
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def get_asr_content(self, audio_data):
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"""Get the streaming asr result
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Args:
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audio_data (_type_): _description_
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Returns:
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_type_: _description_
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"""
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logger.debug("send a message to the server")
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if self.url is None:
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logger.error("No asr server, please input valid ip and port")
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return ""
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ws = websocket.WebSocket()
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logger.debug(f"set the ping timeout: {self.ping_timeout} seconds")
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ws.connect(self.url, ping_timeout=self.ping_timeout)
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audio_info = json.dumps(
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{
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"name": "test.wav",
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"signal": "start",
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"nbest": 1
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},
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sort_keys=True,
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indent=4,
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separators=(',', ': '))
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ws.send(audio_info)
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msg = ws.recv()
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logger.info("client receive msg={}".format(msg))
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# send the total audio data
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for chunk_data in self.read_wave(audio_data):
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ws.send_binary(chunk_data.tobytes())
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msg = ws.recv()
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msg = json.loads(msg)
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logger.info(f"audio result: {msg}")
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# 3. send chunk audio data to engine
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logger.debug("send the end signal")
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audio_info = json.dumps(
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{
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"name": "test.wav",
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"signal": "end",
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"nbest": 1
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},
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sort_keys=True,
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indent=4,
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separators=(',', ': '))
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ws.send(audio_info)
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msg = ws.recv()
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msg = json.loads(msg)
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logger.info(f"the final result: {msg}")
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ws.close()
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return msg
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def read_wave(self, audio_data: str):
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"""read the audio file from specific wavfile path
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Args:
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audio_data (str): the audio data,
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we assume that audio sample rate matches the model
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Yields:
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numpy.array: the samall package audio pcm data
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"""
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samples, sample_rate = soundfile.read(audio_data, dtype='int16')
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x_len = len(samples)
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assert sample_rate == 16000
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chunk_size = int(85 * sample_rate / 1000) # 85ms, sample_rate = 16kHz
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if x_len % chunk_size != 0:
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padding_len_x = chunk_size - x_len % chunk_size
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else:
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padding_len_x = 0
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padding = np.zeros((padding_len_x), dtype=samples.dtype)
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padded_x = np.concatenate([samples, padding], axis=0)
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assert (x_len + padding_len_x) % chunk_size == 0
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num_chunk = (x_len + padding_len_x) / chunk_size
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num_chunk = int(num_chunk)
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for i in range(0, num_chunk):
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start = i * chunk_size
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end = start + chunk_size
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x_chunk = padded_x[start:end]
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yield x_chunk
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def get_macthed_word(self, msg):
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"""Get the matched info in msg
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Args:
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msg (dict): the asr info, including the asr result and time stamp
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Returns:
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acs_result, asr_result: the acs result and the asr result
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"""
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asr_result = msg['result']
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time_stamp = msg['times']
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acs_result = []
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# search for each word in self.word_list
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offset = self.config.offset
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# last time in time_stamp
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max_ed = time_stamp[-1]['ed']
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for w in self.word_list:
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# search the w in asr_result and the index in asr_result
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# https://docs.python.org/3/library/re.html#re.finditer
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for m in re.finditer(w, asr_result):
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# match start and end char index in timestamp
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# https://docs.python.org/3/library/re.html#re.Match.start
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start = max(time_stamp[m.start(0)]['bg'] - offset, 0)
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end = min(time_stamp[m.end(0) - 1]['ed'] + offset, max_ed)
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logger.debug(f'start: {start}, end: {end}')
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acs_result.append({'w': w, 'bg': start, 'ed': end})
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return acs_result, asr_result
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def run(self, audio_data):
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"""process the audio data in acs engine
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the engine does not store any data, so all the request use the self.run api
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Args:
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audio_data (str): the audio data
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Returns:
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acs_result, asr_result: the acs result and the asr result
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"""
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logger.debug("start to process the audio content search")
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msg = self.get_asr_content(io.BytesIO(audio_data))
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acs_result, asr_result = self.get_macthed_word(msg)
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logger.info(f'the asr result {asr_result}')
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logger.info(f'the acs result: {acs_result}')
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return acs_result, asr_result
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