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3 years ago
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# 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 collections
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import json
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import os
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from typing import List
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from typing import Tuple
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from .dataset import AudioClassificationDataset
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__all__ = ['HeySnips']
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class HeySnips(AudioClassificationDataset):
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meta_info = collections.namedtuple('META_INFO',
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('key', 'label', 'duration', 'wav'))
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def __init__(self,
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data_dir: os.PathLike,
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mode: str='train',
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feat_type: str='kaldi_fbank',
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sample_rate: int=16000,
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**kwargs):
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self.data_dir = data_dir
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files, labels = self._get_data(mode)
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super(HeySnips, self).__init__(
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files=files,
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labels=labels,
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feat_type=feat_type,
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sample_rate=sample_rate,
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**kwargs)
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def _get_meta_info(self, mode) -> List[collections.namedtuple]:
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ret = []
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with open(os.path.join(self.data_dir, '{}.json'.format(mode)),
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'r') as f:
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data = json.load(f)
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for item in data:
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sample = collections.OrderedDict()
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if item['duration'] > 0:
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sample['key'] = item['id']
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sample['label'] = 0 if item['is_hotword'] == 1 else -1
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sample['duration'] = item['duration']
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sample['wav'] = os.path.join(self.data_dir,
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item['audio_file_path'])
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ret.append(self.meta_info(*sample.values()))
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return ret
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def _get_data(self, mode: str) -> Tuple[List[str], List[int]]:
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meta_info = self._get_meta_info(mode)
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files = []
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labels = []
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self.keys = []
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self.durations = []
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for sample in meta_info:
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key, target, duration, wav = sample
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files.append(wav)
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labels.append(int(target))
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self.keys.append(key)
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self.durations.append(float(duration))
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return files, labels
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([简体中文](./README_cn.md)|English)
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# Speech Server
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## Introduction
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This demo is an implementation of starting the streaming speech service and accessing the service. It can be achieved with a single command using `paddlespeech_server` and `paddlespeech_client` or a few lines of code in python.
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Streaming ASR server only support `websocket` protocol, and doesn't support `http` protocol.
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## Usage
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### 1. Installation
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see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
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It is recommended to use **paddlepaddle 2.2.1** or above.
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You can choose one way from meduim and hard to install paddlespeech.
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### 2. Prepare config File
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The configuration file can be found in `conf/ws_application.yaml` 和 `conf/ws_conformer_application.yaml`.
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At present, the speech tasks integrated by the model include: DeepSpeech2 and conformer.
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The input of ASR client demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
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Here are sample files for thisASR client demo that can be downloaded:
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```bash
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wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
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```
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### 3. Server Usage
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- Command Line (Recommended)
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```bash
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# in PaddleSpeech/demos/streaming_asr_server start the service
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paddlespeech_server start --config_file ./conf/ws_conformer_application.yaml
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```
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Usage:
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```bash
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paddlespeech_server start --help
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```
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Arguments:
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- `config_file`: yaml file of the app, defalut: `./conf/application.yaml`
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- `log_file`: log file. Default: `./log/paddlespeech.log`
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Output:
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```bash
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[2022-04-21 15:52:18,126] [ INFO] - create the online asr engine instance
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[2022-04-21 15:52:18,127] [ INFO] - paddlespeech_server set the device: cpu
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[2022-04-21 15:52:18,128] [ INFO] - Load the pretrained model, tag = conformer_online_multicn-zh-16k
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[2022-04-21 15:52:18,128] [ INFO] - File /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/asr1_chunk_conformer_multi_cn_ckpt_0.2.3.model.tar.gz md5 checking...
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[2022-04-21 15:52:18,727] [ INFO] - Use pretrained model stored in: /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k
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[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k
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[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/model.yaml
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[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/exp/chunk_conformer/checkpoints/multi_cn.pdparams
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[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/exp/chunk_conformer/checkpoints/multi_cn.pdparams
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[2022-04-21 15:52:19,446] [ INFO] - start to create the stream conformer asr engine
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[2022-04-21 15:52:19,473] [ INFO] - model name: conformer_online
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
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[2022-04-21 15:52:21,731] [ INFO] - create the transformer like model success
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[2022-04-21 15:52:21,733] [ INFO] - Initialize ASR server engine successfully.
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INFO: Started server process [11173]
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[2022-04-21 15:52:21] [INFO] [server.py:75] Started server process [11173]
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INFO: Waiting for application startup.
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[2022-04-21 15:52:21] [INFO] [on.py:45] Waiting for application startup.
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INFO: Application startup complete.
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[2022-04-21 15:52:21] [INFO] [on.py:59] Application startup complete.
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/home/users/xiongxinlei/.conda/envs/paddlespeech/lib/python3.9/asyncio/base_events.py:1460: DeprecationWarning: The loop argument is deprecated since Python 3.8, and scheduled for removal in Python 3.10.
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infos = await tasks.gather(*fs, loop=self)
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/home/users/xiongxinlei/.conda/envs/paddlespeech/lib/python3.9/asyncio/base_events.py:1518: DeprecationWarning: The loop argument is deprecated since Python 3.8, and scheduled for removal in Python 3.10.
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await tasks.sleep(0, loop=self)
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INFO: Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
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[2022-04-21 15:52:21] [INFO] [server.py:206] Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
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```
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- Python API
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```python
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# in PaddleSpeech/demos/streaming_asr_server directory
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from paddlespeech.server.bin.paddlespeech_server import ServerExecutor
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server_executor = ServerExecutor()
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server_executor(
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config_file="./conf/ws_conformer_application.yaml",
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log_file="./log/paddlespeech.log")
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```
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Output:
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```bash
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[2022-04-21 15:52:18,126] [ INFO] - create the online asr engine instance
|
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[2022-04-21 15:52:18,127] [ INFO] - paddlespeech_server set the device: cpu
|
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[2022-04-21 15:52:18,128] [ INFO] - Load the pretrained model, tag = conformer_online_multicn-zh-16k
|
||||
[2022-04-21 15:52:18,128] [ INFO] - File /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/asr1_chunk_conformer_multi_cn_ckpt_0.2.3.model.tar.gz md5 checking...
|
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[2022-04-21 15:52:18,727] [ INFO] - Use pretrained model stored in: /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k
|
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[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k
|
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[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/model.yaml
|
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[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/exp/chunk_conformer/checkpoints/multi_cn.pdparams
|
||||
[2022-04-21 15:52:18,727] [ INFO] - /home/users/xiongxinlei/.paddlespeech/models/conformer_online_multicn-zh-16k/exp/chunk_conformer/checkpoints/multi_cn.pdparams
|
||||
[2022-04-21 15:52:19,446] [ INFO] - start to create the stream conformer asr engine
|
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[2022-04-21 15:52:19,473] [ INFO] - model name: conformer_online
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set kaiming_uniform
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set kaiming_uniform
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
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set kaiming_uniform
|
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set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
||||
set kaiming_uniform
|
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set kaiming_uniform
|
||||
[2022-04-21 15:52:21,731] [ INFO] - create the transformer like model success
|
||||
[2022-04-21 15:52:21,733] [ INFO] - Initialize ASR server engine successfully.
|
||||
INFO: Started server process [11173]
|
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[2022-04-21 15:52:21] [INFO] [server.py:75] Started server process [11173]
|
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INFO: Waiting for application startup.
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||||
[2022-04-21 15:52:21] [INFO] [on.py:45] Waiting for application startup.
|
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INFO: Application startup complete.
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[2022-04-21 15:52:21] [INFO] [on.py:59] Application startup complete.
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/home/users/xiongxinlei/.conda/envs/paddlespeech/lib/python3.9/asyncio/base_events.py:1460: DeprecationWarning: The loop argument is deprecated since Python 3.8, and scheduled for removal in Python 3.10.
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infos = await tasks.gather(*fs, loop=self)
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/home/users/xiongxinlei/.conda/envs/paddlespeech/lib/python3.9/asyncio/base_events.py:1518: DeprecationWarning: The loop argument is deprecated since Python 3.8, and scheduled for removal in Python 3.10.
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await tasks.sleep(0, loop=self)
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INFO: Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
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[2022-04-21 15:52:21] [INFO] [server.py:206] Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
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```
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### 4. ASR Client Usage
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**Note:** The response time will be slightly longer when using the client for the first time
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- Command Line (Recommended)
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```
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paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
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```
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Usage:
|
||||
|
||||
```bash
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paddlespeech_client asr_online --help
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```
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Arguments:
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- `server_ip`: server ip. Default: 127.0.0.1
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- `port`: server port. Default: 8090
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- `input`(required): Audio file to be recognized.
|
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- `sample_rate`: Audio ampling rate, default: 16000.
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- `lang`: Language. Default: "zh_cn".
|
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- `audio_format`: Audio format. Default: "wav".
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- `punc.server_ip`: punctuation server ip. Default: None.
|
||||
- `punc.server_port`: punctuation server port. Default: None.
|
||||
|
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Output:
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||||
```bash
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||||
[2022-04-21 15:59:03,904] [ INFO] - receive msg={"status": "ok", "signal": "server_ready"}
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||||
[2022-04-21 15:59:03,960] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:03,973] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:03,987] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,000] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,012] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,024] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,036] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,047] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,607] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,620] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,633] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,645] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,657] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,669] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,680] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:05,176] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,185] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,192] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,200] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,208] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,216] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,224] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,232] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,724] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,732] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,740] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,747] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,755] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,763] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,770] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:06,271] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,279] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,287] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,294] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,302] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,310] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,318] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,326] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,833] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,842] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,850] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,858] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,866] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,874] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,882] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:07,400] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,408] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,416] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,424] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,432] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,440] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,447] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,455] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,984] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:07,992] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,001] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,008] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,016] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,024] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:12,883] [ INFO] - final receive msg={'status': 'ok', 'signal': 'finished', 'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:12,884] [ INFO] - 我认为跑步最重要的就是给我带来了身体健康
|
||||
[2022-04-21 15:59:12,884] [ INFO] - Response time 9.051567 s.
|
||||
|
||||
```
|
||||
|
||||
- Python API
|
||||
```python
|
||||
from paddlespeech.server.bin.paddlespeech_client import ASROnlineClientExecutor
|
||||
|
||||
asrclient_executor = ASROnlineClientExecutor()
|
||||
res = asrclient_executor(
|
||||
input="./zh.wav",
|
||||
server_ip="127.0.0.1",
|
||||
port=8090,
|
||||
sample_rate=16000,
|
||||
lang="zh_cn",
|
||||
audio_format="wav")
|
||||
print(res)
|
||||
```
|
||||
|
||||
Output:
|
||||
```bash
|
||||
[2022-04-21 15:59:03,904] [ INFO] - receive msg={"status": "ok", "signal": "server_ready"}
|
||||
[2022-04-21 15:59:03,960] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:03,973] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:03,987] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,000] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,012] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,024] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,036] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,047] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,607] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,620] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,633] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,645] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,657] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,669] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:04,680] [ INFO] - receive msg={'asr_results': ''}
|
||||
[2022-04-21 15:59:05,176] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,185] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,192] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,200] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,208] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,216] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,224] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,232] [ INFO] - receive msg={'asr_results': '我认为跑'}
|
||||
[2022-04-21 15:59:05,724] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,732] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,740] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,747] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,755] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,763] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:05,770] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的'}
|
||||
[2022-04-21 15:59:06,271] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,279] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,287] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,294] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,302] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,310] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,318] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,326] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是'}
|
||||
[2022-04-21 15:59:06,833] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,842] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,850] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,858] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,866] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,874] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:06,882] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给'}
|
||||
[2022-04-21 15:59:07,400] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,408] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,416] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,424] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,432] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,440] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,447] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,455] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了'}
|
||||
[2022-04-21 15:59:07,984] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:07,992] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,001] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,008] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,016] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:08,024] [ INFO] - receive msg={'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
[2022-04-21 15:59:12,883] [ INFO] - final receive msg={'status': 'ok', 'signal': 'finished', 'asr_results': '我认为跑步最重要的就是给我带来了身体健康'}
|
||||
```
|
||||
@ -0,0 +1,45 @@
|
||||
# This is the parameter configuration file for PaddleSpeech Serving.
|
||||
|
||||
#################################################################################
|
||||
# SERVER SETTING #
|
||||
#################################################################################
|
||||
host: 0.0.0.0
|
||||
port: 8090
|
||||
|
||||
# The task format in the engin_list is: <speech task>_<engine type>
|
||||
# task choices = ['asr_online']
|
||||
# protocol = ['websocket'] (only one can be selected).
|
||||
# websocket only support online engine type.
|
||||
protocol: 'websocket'
|
||||
engine_list: ['asr_online']
|
||||
|
||||
|
||||
#################################################################################
|
||||
# ENGINE CONFIG #
|
||||
#################################################################################
|
||||
|
||||
################################### ASR #########################################
|
||||
################### speech task: asr; engine_type: online #######################
|
||||
asr_online:
|
||||
model_type: 'conformer_online_multicn'
|
||||
am_model: # the pdmodel file of am static model [optional]
|
||||
am_params: # the pdiparams file of am static model [optional]
|
||||
lang: 'zh'
|
||||
sample_rate: 16000
|
||||
cfg_path:
|
||||
decode_method:
|
||||
force_yes: True
|
||||
device: # cpu or gpu:id
|
||||
am_predictor_conf:
|
||||
device: # set 'gpu:id' or 'cpu'
|
||||
switch_ir_optim: True
|
||||
glog_info: False # True -> print glog
|
||||
summary: True # False -> do not show predictor config
|
||||
|
||||
chunk_buffer_conf:
|
||||
window_n: 7 # frame
|
||||
shift_n: 4 # frame
|
||||
window_ms: 25 # ms
|
||||
shift_ms: 10 # ms
|
||||
sample_rate: 16000
|
||||
sample_width: 2
|
||||
@ -0,0 +1,47 @@
|
||||
# This is the parameter configuration file for PaddleSpeech Serving.
|
||||
|
||||
#################################################################################
|
||||
# SERVER SETTING #
|
||||
#################################################################################
|
||||
host: 0.0.0.0
|
||||
port: 8090
|
||||
|
||||
# The task format in the engin_list is: <speech task>_<engine type>
|
||||
# task choices = ['asr_online']
|
||||
# protocol = ['websocket'] (only one can be selected).
|
||||
# websocket only support online engine type.
|
||||
protocol: 'websocket'
|
||||
engine_list: ['asr_online']
|
||||
|
||||
|
||||
#################################################################################
|
||||
# ENGINE CONFIG #
|
||||
#################################################################################
|
||||
|
||||
################################### ASR #########################################
|
||||
################### speech task: asr; engine_type: online #######################
|
||||
asr_online:
|
||||
model_type: 'deepspeech2online_aishell'
|
||||
am_model: # the pdmodel file of am static model [optional]
|
||||
am_params: # the pdiparams file of am static model [optional]
|
||||
lang: 'zh'
|
||||
sample_rate: 16000
|
||||
cfg_path:
|
||||
decode_method:
|
||||
force_yes: True
|
||||
|
||||
am_predictor_conf:
|
||||
device: # set 'gpu:id' or 'cpu'
|
||||
switch_ir_optim: True
|
||||
glog_info: False # True -> print glog
|
||||
summary: True # False -> do not show predictor config
|
||||
|
||||
chunk_buffer_conf:
|
||||
frame_duration_ms: 80
|
||||
shift_ms: 40
|
||||
sample_rate: 16000
|
||||
sample_width: 2
|
||||
window_n: 7 # frame
|
||||
shift_n: 4 # frame
|
||||
window_ms: 20 # ms
|
||||
shift_ms: 10 # ms
|
||||
@ -0,0 +1,45 @@
|
||||
# This is the parameter configuration file for PaddleSpeech Serving.
|
||||
|
||||
#################################################################################
|
||||
# SERVER SETTING #
|
||||
#################################################################################
|
||||
host: 0.0.0.0
|
||||
port: 8090
|
||||
|
||||
# The task format in the engin_list is: <speech task>_<engine type>
|
||||
# task choices = ['asr_online']
|
||||
# protocol = ['websocket'] (only one can be selected).
|
||||
# websocket only support online engine type.
|
||||
protocol: 'websocket'
|
||||
engine_list: ['asr_online']
|
||||
|
||||
|
||||
#################################################################################
|
||||
# ENGINE CONFIG #
|
||||
#################################################################################
|
||||
|
||||
################################### ASR #########################################
|
||||
################### speech task: asr; engine_type: online #######################
|
||||
asr_online:
|
||||
model_type: 'conformer_online_multicn'
|
||||
am_model: # the pdmodel file of am static model [optional]
|
||||
am_params: # the pdiparams file of am static model [optional]
|
||||
lang: 'zh'
|
||||
sample_rate: 16000
|
||||
cfg_path:
|
||||
decode_method:
|
||||
force_yes: True
|
||||
device: # cpu or gpu:id
|
||||
am_predictor_conf:
|
||||
device: # set 'gpu:id' or 'cpu'
|
||||
switch_ir_optim: True
|
||||
glog_info: False # True -> print glog
|
||||
summary: True # False -> do not show predictor config
|
||||
|
||||
chunk_buffer_conf:
|
||||
window_n: 7 # frame
|
||||
shift_n: 4 # frame
|
||||
window_ms: 25 # ms
|
||||
shift_ms: 10 # ms
|
||||
sample_rate: 16000
|
||||
sample_width: 2
|
||||
@ -0,0 +1,2 @@
|
||||
# start the streaming asr service
|
||||
paddlespeech_server start --config_file ./conf/ws_conformer_application.yaml
|
||||
@ -0,0 +1,5 @@
|
||||
# download the test wav
|
||||
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
|
||||
|
||||
# read the wav and pass it to service
|
||||
python3 websocket_client.py --wavfile ./zh.wav
|
||||
|
Before Width: | Height: | Size: 949 KiB After Width: | Height: | Size: 949 KiB |
|
Before Width: | Height: | Size: 432 KiB After Width: | Height: | Size: 432 KiB |
|
Before Width: | Height: | Size: 72 KiB After Width: | Height: | Size: 72 KiB |
|
Before Width: | Height: | Size: 286 KiB After Width: | Height: | Size: 286 KiB |
Some files were not shown because too many files have changed in this diff Show More
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Reference in new issue