提交 90306065 编写于 作者: X xiongxinlei

update the acs server config, test=doc

上级 25ee9605
......@@ -2,9 +2,9 @@
# ACS (Audio Content Search)
## Introduction
ACS, or Audio Content Search, refers to the problem of getting the key word time stamp to from automatically transcribe spoken language (speech-to-text).
ACS, or Audio Content Search, refers to the problem of getting the key word time stamp from automatically transcribe spoken language (speech-to-text).
This demo is an implementation to get the key word stamp from the text from a specific audio file. It can be done by a single command or a few lines in python using `PaddleSpeech`.
This demo is an implementation of obtaining the keyword timestamp in the text from a given audio file. It can be done by a single command or a few lines in python using `PaddleSpeech`.
## Usage
### 1. Installation
......@@ -12,6 +12,7 @@ see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/doc
You can choose one way from meduim and hard to install paddlespeech.
The dependency refers to the requirements.txt
### 2. Prepare Input File
The input of this demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
......
......@@ -11,6 +11,7 @@
请看[安装文档](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install_cn.md)
你可以从 medium,hard 三中方式中选择一种方式安装。
依赖参见 requirements.txt
### 2. 准备输入
这个 demo 的输入应该是一个 WAV 文件(`.wav`),并且采样率必须与模型的采样率相同。
......
# This is the parameter configuration file for PaddleSpeech Serving.
#################################################################################
# SERVER SETTING #
#################################################################################
......@@ -18,8 +16,8 @@ engine_list: ['acs_python']
# ENGINE CONFIG #
#################################################################################
################################### Text #########################################
################### acs task: engine_type: python #######################
################################### ACS #########################################
################### acs task: engine_type: python ###############################
acs_python:
task: acs
asr_protocol: 'websocket' # 'websocket'
......
# This is the parameter configuration file for PaddleSpeech Serving.
#################################################################################
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8090
port: 8390
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online']
......@@ -27,7 +25,7 @@ asr_online:
lang: 'zh'
sample_rate: 16000
cfg_path:
decode_method:
decode_method: 'attention_rescoring'
force_yes: True
device: 'cpu' # cpu or gpu:id
am_predictor_conf:
......
export CUDA_VISIBLE_DEVICE=0,1,2,3
#nohup python3 streaming_asr_server.py --config_file conf/ws_conformer_application.yaml &> streaming_asr.log &
# we need the streaming asr server
nohup python3 streaming_asr_server.py --config_file conf/ws_conformer_application.yaml > streaming_asr.log 2>&1 &
# nohup python3 punc_server.py --config_file conf/punc_application.yaml > punc.log 2>&1 &
paddlespeech_server start --config_file conf/acs_application.yaml
# start the acs server
nohup paddlespeech_server start --config_file conf/acs_application.yaml > acs.log 2>&1 &
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