([简体中文](./README_cn.md)|English) # Streaming Speech Synthesis Service ## Introduction This demo is an implementation of starting the streaming speech synthesis 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. For service interface definition, please check: - [PaddleSpeech Server RESTful API](https://github.com/PaddlePaddle/PaddleSpeech/wiki/PaddleSpeech-Server-RESTful-API) - [PaddleSpeech Streaming Server WebSocket API](https://github.com/PaddlePaddle/PaddleSpeech/wiki/PaddleSpeech-Server-WebSocket-API) ## Usage ### 1. Installation see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md). It is recommended to use **paddlepaddle 2.3.1** or above. You can choose one way from easy, meduim and hard to install paddlespeech. **If you install in easy mode, you need to prepare the yaml file by yourself, you can refer to the yaml file in the conf directory.** ### 2. Prepare config File The configuration file can be found in `conf/tts_online_application.yaml`. - `protocol` indicates the network protocol used by the streaming TTS service. Currently, both **http and websocket** are supported. - `engine_list` indicates the speech engine that will be included in the service to be started, in the format of `_`. - This demo mainly introduces the streaming speech synthesis service, so the speech task should be set to `tts`. - the engine type supports two forms: **online** and **online-onnx**. `online` indicates an engine that uses python for dynamic graph inference; `online-onnx` indicates an engine that uses onnxruntime for inference. The inference speed of online-onnx is faster. - Streaming TTS engine AM model support: **fastspeech2 and fastspeech2_cnndecoder**; Voc model support: **hifigan and mb_melgan** - In streaming am inference, one chunk of data is inferred at a time to achieve a streaming effect. Among them, `am_block` indicates the number of valid frames in the chunk, and `am_pad` indicates the number of frames added before and after am_block in a chunk. The existence of am_pad is used to eliminate errors caused by streaming inference and avoid the influence of streaming inference on the quality of synthesized audio. - fastspeech2 does not support streaming am inference, so am_pad and am_block have no effect on it. - fastspeech2_cnndecoder supports streaming inference. When am_pad=12, streaming inference synthesized audio is consistent with non-streaming synthesized audio. - In streaming voc inference, one chunk of data is inferred at a time to achieve a streaming effect. Where `voc_block` indicates the number of valid frames in the chunk, and `voc_pad` indicates the number of frames added before and after the voc_block in a chunk. The existence of voc_pad is used to eliminate errors caused by streaming inference and avoid the influence of streaming inference on the quality of synthesized audio. - Both hifigan and mb_melgan support streaming voc inference. - When the voc model is mb_melgan, when voc_pad=14, the synthetic audio for streaming inference is consistent with the non-streaming synthetic audio; the minimum voc_pad can be set to 7, and the synthetic audio has no abnormal hearing. If the voc_pad is less than 7, the synthetic audio sounds abnormal. - When the voc model is hifigan, when voc_pad=19, the streaming inference synthetic audio is consistent with the non-streaming synthetic audio; when voc_pad=14, the synthetic audio has no abnormal hearing. - Pad calculation method of streaming vocoder in PaddleSpeech: [AIStudio tutorial](https://aistudio.baidu.com/aistudio/projectdetail/4151335) - Inference speed: mb_melgan > hifigan; Audio quality: mb_melgan < hifigan - **Note:** If the service can be started normally in the container, but the client access IP is unreachable, you can try to replace the `host` address in the configuration file with the local IP address. ### 3. Streaming speech synthesis server and client using http protocol #### 3.1 Server Usage - Command Line (Recommended) Start the service (the configuration file uses http by default): ```bash paddlespeech_server start --config_file ./conf/tts_online_application.yaml ``` Usage: ```bash paddlespeech_server start --help ``` Arguments: - `config_file`: yaml file of the app, defalut: ./conf/tts_online_application.yaml - `log_file`: log file. Default: ./log/paddlespeech.log Output: ```text [2022-04-24 20:05:27,887] [ INFO] - The first response time of the 0 warm up: 1.0123658180236816 s [2022-04-24 20:05:28,038] [ INFO] - The first response time of the 1 warm up: 0.15108466148376465 s [2022-04-24 20:05:28,191] [ INFO] - The first response time of the 2 warm up: 0.15317344665527344 s [2022-04-24 20:05:28,192] [ INFO] - ********************************************************************** INFO: Started server process [14638] [2022-04-24 20:05:28] [INFO] [server.py:75] Started server process [14638] INFO: Waiting for application startup. [2022-04-24 20:05:28] [INFO] [on.py:45] Waiting for application startup. INFO: Application startup complete. [2022-04-24 20:05:28] [INFO] [on.py:59] Application startup complete. INFO: Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) [2022-04-24 20:05:28] [INFO] [server.py:211] Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) ``` - Python API ```python from paddlespeech.server.bin.paddlespeech_server import ServerExecutor server_executor = ServerExecutor() server_executor( config_file="./conf/tts_online_application.yaml", log_file="./log/paddlespeech.log") ``` Output: ```text [2022-04-24 21:00:16,934] [ INFO] - The first response time of the 0 warm up: 1.268730878829956 s [2022-04-24 21:00:17,046] [ INFO] - The first response time of the 1 warm up: 0.11168622970581055 s [2022-04-24 21:00:17,151] [ INFO] - The first response time of the 2 warm up: 0.10413002967834473 s [2022-04-24 21:00:17,151] [ INFO] - ********************************************************************** INFO: Started server process [320] [2022-04-24 21:00:17] [INFO] [server.py:75] Started server process [320] INFO: Waiting for application startup. [2022-04-24 21:00:17] [INFO] [on.py:45] Waiting for application startup. INFO: Application startup complete. [2022-04-24 21:00:17] [INFO] [on.py:59] Application startup complete. INFO: Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) [2022-04-24 21:00:17] [INFO] [server.py:211] Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) ``` #### 3.2 Streaming TTS client Usage - Command Line (Recommended) Access http streaming TTS service: If `127.0.0.1` is not accessible, you need to use the actual service IP address. ```bash paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol http --input "您好,欢迎使用百度飞桨语音合成服务。" --output output.wav ``` Usage: ```bash paddlespeech_client tts_online --help ``` Arguments: - `server_ip`: erver ip. Default: 127.0.0.1 - `port`: server port. Default: 8092 - `protocol`: Service protocol, choices: [http, websocket], default: http. - `input`: (required): Input text to generate. - `spk_id`: Speaker id for multi-speaker text to speech. Default: 0 - `output`: Client output wave filepath. Default: None, which means not to save the audio to the local. - `play`: Whether to play audio, play while synthesizing, default value: False, which means not playing. **Playing audio needs to rely on the pyaudio library**. - Currently, only the single-speaker model is supported in the code, so `spk_id` does not take effect. Streaming TTS does not support changing sample rate, variable speed and volume. Output: ```text [2022-04-24 21:08:18,559] [ INFO] - tts http client start [2022-04-24 21:08:21,702] [ INFO] - 句子:您好,欢迎使用百度飞桨语音合成服务。 [2022-04-24 21:08:21,703] [ INFO] - 首包响应:0.18863153457641602 s [2022-04-24 21:08:21,704] [ INFO] - 尾包响应:3.1427218914031982 s [2022-04-24 21:08:21,704] [ INFO] - 音频时长:3.825 s [2022-04-24 21:08:21,704] [ INFO] - RTF: 0.8216266382753459 [2022-04-24 21:08:21,739] [ INFO] - 音频保存至:output.wav ``` - Python API ```python from paddlespeech.server.bin.paddlespeech_client import TTSOnlineClientExecutor import json executor = TTSOnlineClientExecutor() executor( input="您好,欢迎使用百度飞桨语音合成服务。", server_ip="127.0.0.1", port=8092, protocol="http", spk_id=0, output="./output.wav", play=False) ``` Output: ```text [2022-04-24 21:11:13,798] [ INFO] - tts http client start [2022-04-24 21:11:16,800] [ INFO] - 句子:您好,欢迎使用百度飞桨语音合成服务。 [2022-04-24 21:11:16,801] [ INFO] - 首包响应:0.18234872817993164 s [2022-04-24 21:11:16,801] [ INFO] - 尾包响应:3.0013909339904785 s [2022-04-24 21:11:16,802] [ INFO] - 音频时长:3.825 s [2022-04-24 21:11:16,802] [ INFO] - RTF: 0.7846773683635238 [2022-04-24 21:11:16,837] [ INFO] - 音频保存至:./output.wav ``` ### 4. Streaming speech synthesis server and client using websocket protocol #### 4.1 Server Usage - Command Line (Recommended) First modify the configuration file `conf/tts_online_application.yaml`, **set `protocol` to `websocket`**. Start the service: ```bash paddlespeech_server start --config_file ./conf/tts_online_application.yaml ``` Usage: ```bash paddlespeech_server start --help ``` Arguments: - `config_file`: yaml file of the app, defalut: ./conf/tts_online_application.yaml - `log_file`: log file. Default: ./log/paddlespeech.log Output: ```text [2022-04-27 10:18:09,107] [ INFO] - The first response time of the 0 warm up: 1.1551103591918945 s [2022-04-27 10:18:09,219] [ INFO] - The first response time of the 1 warm up: 0.11204338073730469 s [2022-04-27 10:18:09,324] [ INFO] - The first response time of the 2 warm up: 0.1051797866821289 s [2022-04-27 10:18:09,325] [ INFO] - ********************************************************************** INFO: Started server process [17600] [2022-04-27 10:18:09] [INFO] [server.py:75] Started server process [17600] INFO: Waiting for application startup. [2022-04-27 10:18:09] [INFO] [on.py:45] Waiting for application startup. INFO: Application startup complete. [2022-04-27 10:18:09] [INFO] [on.py:59] Application startup complete. INFO: Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) [2022-04-27 10:18:09] [INFO] [server.py:211] Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) ``` - Python API ```python from paddlespeech.server.bin.paddlespeech_server import ServerExecutor server_executor = ServerExecutor() server_executor( config_file="./conf/tts_online_application.yaml", log_file="./log/paddlespeech.log") ``` Output: ```text [2022-04-27 10:20:16,660] [ INFO] - The first response time of the 0 warm up: 1.0945196151733398 s [2022-04-27 10:20:16,773] [ INFO] - The first response time of the 1 warm up: 0.11222052574157715 s [2022-04-27 10:20:16,878] [ INFO] - The first response time of the 2 warm up: 0.10494542121887207 s [2022-04-27 10:20:16,878] [ INFO] - ********************************************************************** INFO: Started server process [23466] [2022-04-27 10:20:16] [INFO] [server.py:75] Started server process [23466] INFO: Waiting for application startup. [2022-04-27 10:20:16] [INFO] [on.py:45] Waiting for application startup. INFO: Application startup complete. [2022-04-27 10:20:16] [INFO] [on.py:59] Application startup complete. INFO: Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) [2022-04-27 10:20:16] [INFO] [server.py:211] Uvicorn running on http://0.0.0.0:8092 (Press CTRL+C to quit) ``` #### 4.2 Streaming TTS client Usage - Command Line (Recommended) Access websocket streaming TTS service: If `127.0.0.1` is not accessible, you need to use the actual service IP address. ```bash paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol websocket --input "您好,欢迎使用百度飞桨语音合成服务。" --output output.wav ``` Usage: ```bash paddlespeech_client tts_online --help ``` Arguments: - `server_ip`: erver ip. Default: 127.0.0.1 - `port`: server port. Default: 8092 - `protocol`: Service protocol, choices: [http, websocket], default: http. - `input`: (required): Input text to generate. - `spk_id`: Speaker id for multi-speaker text to speech. Default: 0 - `output`: Client output wave filepath. Default: None, which means not to save the audio to the local. - `play`: Whether to play audio, play while synthesizing, default value: False, which means not playing. **Playing audio needs to rely on the pyaudio library**. - Currently, only the single-speaker model is supported in the code, so `spk_id` does not take effect. Streaming TTS does not support changing sample rate, variable speed and volume. Output: ```text [2022-04-27 10:21:04,262] [ INFO] - tts websocket client start [2022-04-27 10:21:04,496] [ INFO] - 句子:您好,欢迎使用百度飞桨语音合成服务。 [2022-04-27 10:21:04,496] [ INFO] - 首包响应:0.2124948501586914 s [2022-04-27 10:21:07,483] [ INFO] - 尾包响应:3.199106454849243 s [2022-04-27 10:21:07,484] [ INFO] - 音频时长:3.825 s [2022-04-27 10:21:07,484] [ INFO] - RTF: 0.8363677006141812 [2022-04-27 10:21:07,516] [ INFO] - 音频保存至:output.wav ``` - Python API ```python from paddlespeech.server.bin.paddlespeech_client import TTSOnlineClientExecutor import json executor = TTSOnlineClientExecutor() executor( input="您好,欢迎使用百度飞桨语音合成服务。", server_ip="127.0.0.1", port=8092, protocol="websocket", spk_id=0, output="./output.wav", play=False) ``` Output: ```text [2022-04-27 10:22:48,852] [ INFO] - tts websocket client start [2022-04-27 10:22:49,080] [ INFO] - 句子:您好,欢迎使用百度飞桨语音合成服务。 [2022-04-27 10:22:49,080] [ INFO] - 首包响应:0.21017956733703613 s [2022-04-27 10:22:52,100] [ INFO] - 尾包响应:3.2304444313049316 s [2022-04-27 10:22:52,101] [ INFO] - 音频时长:3.825 s [2022-04-27 10:22:52,101] [ INFO] - RTF: 0.8445606356352762 [2022-04-27 10:22:52,134] [ INFO] - 音频保存至:./output.wav ```