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([简体中文](./README_cn.md)|English)
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# ACS (Audio Content Search)
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## Introduction
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ACS, or Audio Content Search, refers to the problem of getting the key word time stamp from automatically transcribe spoken language (speech-to-text).
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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`.
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Now, the search word in demo is:
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```
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我
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康
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```
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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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You can choose one way from meduim and hard to install paddlespeech.
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The dependency refers to the requirements.txt, and install the dependency as follows:
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```
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pip install -r requirements.txt
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```
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### 2. Prepare Input File
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The input of this 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 this 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. run paddlespeech_server
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Before using the client, it is necessary to start paddlespeech_servers.
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Here are sample server configuration：
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```bash
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bash demos/audio_content_search/run.sh
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```
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The logs of the two services will be recorded in 'acs.log' and 'streaming_asr.log' in this configuration.
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### 4. Usage
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- Command Line(Recommended)
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```bash
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# Chinese
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paddlespeech_client acs --server_ip 127.0.0.1 --port 8490 --input ./zh.wav
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```
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Usage:
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```bash
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paddlespeech asr --help
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```
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Arguments:
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- `input`(required): Audio file to recognize.
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- `server_ip`: the server ip.
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- `port`: the server port.
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- `lang`: the language type of the model. Default: `zh`.
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- `sample_rate`: Sample rate of the model. Default: `16000`.
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- `audio_format`: The audio format.
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Output:
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```bash
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[2022-05-15 15:00:58,185] [ INFO] - acs http client start
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[2022-05-15 15:00:58,185] [ INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
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[2022-05-15 15:01:03,220] [ INFO] - acs http client finished
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[2022-05-15 15:01:03,221] [ INFO] - ACS result: {'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}
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[2022-05-15 15:01:03,221] [ INFO] - Response time 5.036084 s.
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```
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- Python API
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```python
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from paddlespeech.server.bin.paddlespeech_client import ACSClientExecutor
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acs_executor = ACSClientExecutor()
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res = acs_executor(
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input='./zh.wav',
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server_ip="127.0.0.1",
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port=8490,)
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print(res)
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```
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Output:
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```bash
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[2022-05-15 15:08:13,955] [ INFO] - acs http client start
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[2022-05-15 15:08:13,956] [ INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
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[2022-05-15 15:08:19,026] [ INFO] - acs http client finished
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{'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}
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```
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