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PaddleSpeech/demos/speech_server/README_cn.md

21 KiB

(简体中文|English)

语音服务

介绍

这个 demo 是一个启动离线语音服务和访问服务的实现。它可以通过使用 paddlespeech_serverpaddlespeech_client 的单个命令或 python 的几行代码来实现。

服务接口定义请参考:

使用方法

1. 安装

请看 安装文档.

推荐使用 paddlepaddle 2.3.1 或以上版本。

你可以从简单,中等,困难 几种方式中选择一种方式安装 PaddleSpeech。

如果使用简单模式安装,需要自行准备 yaml 文件,可参考 conf 目录下的 yaml 文件。

2. 准备配置文件

配置文件可参见 conf/application.yaml 。 其中,engine_list 表示即将启动的服务将会包含的语音引擎,格式为 <语音任务>_<引擎类型>。

目前服务集成的语音任务有: asr (语音识别)、tts (语音合成)、cls (音频分类)、vector (声纹识别)以及 text (文本处理)。

目前引擎类型支持两种形式python 及 inference (Paddle Inference) 注意: 如果在容器里可正常启动服务,但客户端访问 ip 不可达,可尝试将配置文件中 host 地址换成本地 ip 地址。

3. 服务端使用方法

  • 命令行 (推荐使用)

    # 启动服务
    paddlespeech_server start --config_file ./conf/application.yaml
    

    使用方法:

    paddlespeech_server start --help
    

    参数:

    • config_file: 服务的配置文件,默认: ./conf/application.yaml
    • log_file: log 文件. 默认:./log/paddlespeech.log

    输出:

    [2022-02-23 11:17:32] [INFO] [server.py:64] Started server process [6384]
    INFO:     Waiting for application startup.
    [2022-02-23 11:17:32] [INFO] [on.py:26] Waiting for application startup.
    INFO:     Application startup complete.
    [2022-02-23 11:17:32] [INFO] [on.py:38] Application startup complete.
    INFO:     Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
    [2022-02-23 11:17:32] [INFO] [server.py:204] Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_server import ServerExecutor
    
    server_executor = ServerExecutor()
    server_executor(
        config_file="./conf/application.yaml", 
        log_file="./log/paddlespeech.log")
    

    输出:

    INFO:     Started server process [529]
    [2022-02-23 14:57:56] [INFO] [server.py:64] Started server process [529]
    INFO:     Waiting for application startup.
    [2022-02-23 14:57:56] [INFO] [on.py:26] Waiting for application startup.
    INFO:     Application startup complete.
    [2022-02-23 14:57:56] [INFO] [on.py:38] Application startup complete.
    INFO:     Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
    [2022-02-23 14:57:56] [INFO] [server.py:204] Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
    

4. ASR 客户端使用方法

ASR 客户端的输入是一个 WAV 文件(.wav),并且采样率必须与模型的采样率相同。

可以下载 ASR 客户端的示例音频:

wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav

注意: 初次使用客户端时响应时间会略长

  • 命令行 (推荐使用)

    127.0.0.1 不能访问,则需要使用实际服务 IP 地址

    paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
    

    使用帮助:

    paddlespeech_client asr --help
    

    参数:

    • server_ip: 服务端 ip 地址,默认: 127.0.0.1。
    • port: 服务端口,默认: 8090。
    • input(必须输入): 用于识别的音频文件。
    • sample_rate: 音频采样率默认值16000。
    • lang: 模型语言默认值zh_cn。
    • audio_format: 音频格式默认值wav。

    输出:

    [2022-08-01 07:54:01,646] [    INFO] - ASR result: 我认为跑步最重要的就是给我带来了身体健康
    [2022-08-01 07:54:01,646] [    INFO] - Response time 4.898965 s.
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_client import ASRClientExecutor
    
    asrclient_executor = ASRClientExecutor()
    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)
    

    输出:

    我认为跑步最重要的就是给我带来了身体健康
    

5. TTS 客户端使用方法

注意: 初次使用客户端时响应时间会略长

  • 命令行 (推荐使用)

    127.0.0.1 不能访问,则需要使用实际服务 IP 地址

    paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "您好,欢迎使用百度飞桨语音合成服务。" --output output.wav
    

    使用帮助:

    paddlespeech_client tts --help
    

    参数:

    • server_ip: 服务端ip地址默认: 127.0.0.1。
    • port: 服务端口,默认: 8090。
    • input(必须输入): 待合成的文本。
    • spk_id: 说话人 id用于多说话人语音合成默认值 0。
    • speed: 音频速度,该值应设置在 0 到 3 之间。 默认值1.0
    • volume: 音频音量,该值应设置在 0 到 3 之间。 默认值: 1.0
    • sample_rate: 采样率,可选 [0, 8000, 16000],默认与模型相同。 默认值0
    • output: 输出音频的路径, 默认值None表示不保存音频到本地。

    输出:

    [2022-02-23 15:20:37,875] [    INFO] - Save synthesized audio successfully on output.wav.
    [2022-02-23 15:20:37,875] [    INFO] - Audio duration: 3.612500 s.
    [2022-02-23 15:20:37,875] [    INFO] - Response time: 0.348050 s.
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_client import TTSClientExecutor
    import json
    
    ttsclient_executor = TTSClientExecutor()
    res = ttsclient_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=8090,
        spk_id=0,
        speed=1.0,
        volume=1.0,
        sample_rate=0,
        output="./output.wav")
    
    response_dict = res.json()
    print(response_dict["message"])
    print("Save synthesized audio successfully on %s." % (response_dict['result']['save_path']))
    print("Audio duration: %f s." %(response_dict['result']['duration']))
    

    输出:

    {'description': 'success.'}
    Save synthesized audio successfully on ./output.wav.
    Audio duration: 3.612500 s.
    

6. CLS 客户端使用方法

可以下载 CLS 客户端的示例音频:

wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav

注意: 初次使用客户端时响应时间会略长

  • 命令行 (推荐使用)

    127.0.0.1 不能访问,则需要使用实际服务 IP 地址

    paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
    

    使用帮助:

    paddlespeech_client cls --help
    

    参数:

    • server_ip: 服务端 ip 地址,默认: 127.0.0.1。
    • port: 服务端口,默认: 8090。
    • input(必须输入): 用于分类的音频文件。
    • topk: 分类结果的topk。

    输出:

    [2022-03-09 20:44:39,974] [    INFO] - {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'topk': 1, 'results': [{'class_name': 'Speech', 'prob': 0.9027184844017029}]}}
    [2022-03-09 20:44:39,975] [    INFO] - Response time 0.104360 s.
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_client import CLSClientExecutor
    import json
    
    clsclient_executor = CLSClientExecutor()
    res = clsclient_executor(
        input="./zh.wav",
        server_ip="127.0.0.1",
        port=8090,
        topk=1)
    print(res.json())
    

    输出:

    {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'topk': 1, 'results': [{'class_name': 'Speech', 'prob': 0.9027184844017029}]}}
    

7. 声纹客户端使用方法

可以下载声纹客户端的示例音频:

wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
wget -c https://paddlespeech.bj.bcebos.com/vector/audio/123456789.wav

7.1 提取声纹特征

注意: 初次使用客户端时响应时间会略长

  • 命令行 (推荐使用)

    127.0.0.1 不能访问,则需要使用实际服务 IP 地址

    paddlespeech_client vector --task spk  --server_ip 127.0.0.1 --port 8090 --input 85236145389.wav
    

    使用帮助:

    paddlespeech_client vector --help
    

    参数:

    • server_ip: 服务端ip地址默认: 127.0.0.1。
    • port: 服务端口,默认: 8090。
    • input(必须输入): 用于识别的音频文件。
    • task: vector 的任务可选spk或者score。默认是 spk。
    • enroll: 注册音频;。
    • test: 测试音频。

    输出:

    [2022-08-01 09:01:22,151] [    INFO] - vector http client start
    [2022-08-01 09:01:22,152] [    INFO] - the input audio: 85236145389.wav
    [2022-08-01 09:01:22,152] [    INFO] - endpoint: http://127.0.0.1:8090/paddlespeech/vector
    [2022-08-01 09:01:27,093] [    INFO] - {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'vec': [1.4217487573623657, 5.626248836517334, -5.342073440551758, 1.177390217781067, 3.308061122894287, 1.7565997838974, 5.1678876876831055, 10.806346893310547, -3.822679042816162, -5.614130973815918, 2.6238481998443604, -0.8072965741157532, 1.963512659072876, -7.312864780426025, 0.011034967377781868, -9.723127365112305, 0.661963164806366, -6.976816654205322, 10.213465690612793, 7.494767189025879, 2.9105641841888428, 3.894925117492676, 3.7999846935272217, 7.106173992156982, 16.905324935913086, -7.149376392364502, 8.733112335205078, 3.423002004623413, -4.831653118133545, -11.403371810913086, 11.232216835021973, 7.127464771270752, -4.282831192016602, 2.4523589611053467, -5.13075065612793, -18.17765998840332, -2.611666440963745, -11.00034236907959, -6.731431007385254, 1.6564655303955078, 0.7618184685707092, 1.1253058910369873, -2.0838277339935303, 4.725739002227783, -8.782590866088867, -3.5398736000061035, 3.8142387866973877, 5.142062664031982, 2.162053346633911, 4.09642219543457, -6.416221618652344, 12.747454643249512, 1.9429889917373657, -15.152948379516602, 6.417416572570801, 16.097013473510742, -9.716649055480957, -1.9920448064804077, -3.364956855773926, -1.8719490766525269, 11.567351341247559, 3.6978795528411865, 11.258269309997559, 7.442364692687988, 9.183405876159668, 4.528151512145996, -1.2417811155319214, 4.395910263061523, 6.672768592834473, 5.889888763427734, 7.627115249633789, -0.6692016124725342, -11.889703750610352, -9.208883285522461, -7.427401542663574, -3.777655601501465, 6.917237758636475, -9.848749160766602, -2.094479560852051, -5.1351189613342285, 0.49564215540885925, 9.317541122436523, -5.9141845703125, -1.809845209121704, -0.11738205701112747, -7.169270992279053, -1.0578246116638184, -5.721685886383057, -5.117387294769287, 16.137670516967773, -4.473618984222412, 7.66243314743042, -0.5538089871406555, 9.631582260131836, -6.470466613769531, -8.54850959777832, 4.371622085571289, -0.7970349192619324, 4.479003429412842, -2.9758646488189697, 3.2721707820892334, 2.8382749557495117, 5.1345953941345215, -9.19078254699707, -0.5657423138618469, -4.874573230743408, 2.316561460494995, -5.984307289123535, -2.1798791885375977, 0.35541653633117676, -0.3178458511829376, 9.493547439575195, 2.114448070526123, 4.358088493347168, -12.089820861816406, 8.451695442199707, -7.925461769104004, 4.624246120452881, 4.428938388824463, 18.691999435424805, -2.620460033416748, -5.149182319641113, -0.3582168221473694, 8.488557815551758, 4.98148250579834, -9.326834678649902, -2.2544236183166504, 6.64176607131958, 1.2119656801223755, 10.977132797241211, 16.55504035949707, 3.323848247528076, 9.55185317993164, -1.6677050590515137, -0.7953923940658569, -8.605660438537598, -0.4735637903213501, 2.6741855144500732, -5.359188079833984, -2.6673784255981445, 0.6660736799240112, 15.443212509155273, 4.740597724914551, -3.4725306034088135, 11.592561721801758, -2.05450701713562, 1.7361239194869995, -8.26533031463623, -9.304476737976074, 5.406835079193115, -1.5180232524871826, -7.746610641479492, -6.089605331420898, 0.07112561166286469, -0.34904858469963074, -8.649889945983887, -9.998958587646484, -2.5648481845855713, -0.5399898886680603, 2.6018145084381104, -0.31927648186683655, -1.8815231323242188, -2.0721378326416016, -3.4105639457702637, -8.299802780151367, 1.4836379289627075, -15.366002082824707, -8.288193702697754, 3.884773015975952, -3.4876506328582764, 7.362995624542236, 0.4657321572303772, 3.1326000690460205, 12.438883781433105, -1.8337029218673706, 4.532927513122559, 2.726433277130127, 10.145345687866211, -6.521956920623779, 2.8971481323242188, -3.3925881385803223, 5.079156398773193, 7.759725093841553, 4.677562236785889, 5.8457818031311035, 2.4023921489715576, 7.707108974456787, 3.9711389541625977, -6.390035152435303, 6.126871109008789, -3.776031017303467, -11.118141174316406]}}
    [2022-08-01 09:01:27,094] [    INFO] - Response time 4.941739 s.
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_client import VectorClientExecutor
    import json
    
    vectorclient_executor = VectorClientExecutor()
    res = vectorclient_executor(
        input="85236145389.wav",
        server_ip="127.0.0.1",
        port=8090,
        task="spk")
    print(res.json())
    

    输出:

    {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'vec': [1.4217487573623657, 5.626248836517334, -5.342073440551758, 1.177390217781067, 3.308061122894287, 1.7565997838974, 5.1678876876831055, 10.806346893310547, -3.822679042816162, -5.614130973815918, 2.6238481998443604, -0.8072965741157532, 1.963512659072876, -7.312864780426025, 0.011034967377781868, -9.723127365112305, 0.661963164806366, -6.976816654205322, 10.213465690612793, 7.494767189025879, 2.9105641841888428, 3.894925117492676, 3.7999846935272217, 7.106173992156982, 16.905324935913086, -7.149376392364502, 8.733112335205078, 3.423002004623413, -4.831653118133545, -11.403371810913086, 11.232216835021973, 7.127464771270752, -4.282831192016602, 2.4523589611053467, -5.13075065612793, -18.17765998840332, -2.611666440963745, -11.00034236907959, -6.731431007385254, 1.6564655303955078, 0.7618184685707092, 1.1253058910369873, -2.0838277339935303, 4.725739002227783, -8.782590866088867, -3.5398736000061035, 3.8142387866973877, 5.142062664031982, 2.162053346633911, 4.09642219543457, -6.416221618652344, 12.747454643249512, 1.9429889917373657, -15.152948379516602, 6.417416572570801, 16.097013473510742, -9.716649055480957, -1.9920448064804077, -3.364956855773926, -1.8719490766525269, 11.567351341247559, 3.6978795528411865, 11.258269309997559, 7.442364692687988, 9.183405876159668, 4.528151512145996, -1.2417811155319214, 4.395910263061523, 6.672768592834473, 5.889888763427734, 7.627115249633789, -0.6692016124725342, -11.889703750610352, -9.208883285522461, -7.427401542663574, -3.777655601501465, 6.917237758636475, -9.848749160766602, -2.094479560852051, -5.1351189613342285, 0.49564215540885925, 9.317541122436523, -5.9141845703125, -1.809845209121704, -0.11738205701112747, -7.169270992279053, -1.0578246116638184, -5.721685886383057, -5.117387294769287, 16.137670516967773, -4.473618984222412, 7.66243314743042, -0.5538089871406555, 9.631582260131836, -6.470466613769531, -8.54850959777832, 4.371622085571289, -0.7970349192619324, 4.479003429412842, -2.9758646488189697, 3.2721707820892334, 2.8382749557495117, 5.1345953941345215, -9.19078254699707, -0.5657423138618469, -4.874573230743408, 2.316561460494995, -5.984307289123535, -2.1798791885375977, 0.35541653633117676, -0.3178458511829376, 9.493547439575195, 2.114448070526123, 4.358088493347168, -12.089820861816406, 8.451695442199707, -7.925461769104004, 4.624246120452881, 4.428938388824463, 18.691999435424805, -2.620460033416748, -5.149182319641113, -0.3582168221473694, 8.488557815551758, 4.98148250579834, -9.326834678649902, -2.2544236183166504, 6.64176607131958, 1.2119656801223755, 10.977132797241211, 16.55504035949707, 3.323848247528076, 9.55185317993164, -1.6677050590515137, -0.7953923940658569, -8.605660438537598, -0.4735637903213501, 2.6741855144500732, -5.359188079833984, -2.6673784255981445, 0.6660736799240112, 15.443212509155273, 4.740597724914551, -3.4725306034088135, 11.592561721801758, -2.05450701713562, 1.7361239194869995, -8.26533031463623, -9.304476737976074, 5.406835079193115, -1.5180232524871826, -7.746610641479492, -6.089605331420898, 0.07112561166286469, -0.34904858469963074, -8.649889945983887, -9.998958587646484, -2.5648481845855713, -0.5399898886680603, 2.6018145084381104, -0.31927648186683655, -1.8815231323242188, -2.0721378326416016, -3.4105639457702637, -8.299802780151367, 1.4836379289627075, -15.366002082824707, -8.288193702697754, 3.884773015975952, -3.4876506328582764, 7.362995624542236, 0.4657321572303772, 3.1326000690460205, 12.438883781433105, -1.8337029218673706, 4.532927513122559, 2.726433277130127, 10.145345687866211, -6.521956920623779, 2.8971481323242188, -3.3925881385803223, 5.079156398773193, 7.759725093841553, 4.677562236785889, 5.8457818031311035, 2.4023921489715576, 7.707108974456787, 3.9711389541625977, -6.390035152435303, 6.126871109008789, -3.776031017303467, -11.118141174316406]}}
    

7.2 音频声纹打分

注意: 初次使用客户端时响应时间会略长

  • 命令行 (推荐使用)

    127.0.0.1 不能访问,则需要使用实际服务 IP 地址

    paddlespeech_client vector --task score  --server_ip 127.0.0.1 --port 8090 --enroll 85236145389.wav --test 123456789.wav
    

    使用帮助:

    paddlespeech_client vector --help
    

    参数:

    • server_ip: 服务端ip地址默认: 127.0.0.1。
    • port: 服务端口,默认: 8090。
    • input(必须输入): 用于识别的音频文件。
    • task: vector 的任务可选spk或者score。默认是 spk。
    • enroll: 注册音频;。
    • test: 测试音频。

    输出:

    [2022-08-01 09:04:42,275] [    INFO] - vector score http client start
    [2022-08-01 09:04:42,275] [    INFO] - enroll audio: 85236145389.wav, test audio: 123456789.wav
    [2022-08-01 09:04:42,275] [    INFO] - endpoint: http://127.0.0.1:8090/paddlespeech/vector/score
    [2022-08-01 09:04:44,611] [    INFO] - {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.4292638897895813}}
    [2022-08-01 09:04:44,611] [    INFO] - Response time 2.336258 s.
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_client import VectorClientExecutor
    import json
    
    vectorclient_executor = VectorClientExecutor()
    res = vectorclient_executor(
        input=None,
        enroll_audio="85236145389.wav",
        test_audio="123456789.wav",
        server_ip="127.0.0.1",
        port=8090,
        task="score")
    print(res.json())
    

    输出:

    {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.4292638897895813}}
    

8. 标点预测

注意: 初次使用客户端时响应时间会略长

  • 命令行 (推荐使用)

    127.0.0.1 不能访问,则需要使用实际服务 IP 地址

    paddlespeech_client text --server_ip 127.0.0.1 --port 8090 --input "我认为跑步最重要的就是给我带来了身体健康"
    

    使用帮助:

    paddlespeech_client text --help
    

    参数:

    • server_ip: 服务端ip地址默认: 127.0.0.1。
    • port: 服务端口,默认: 8090。
    • input(必须输入): 用于标点预测的文本内容。

    输出:

    [2022-05-09 18:19:04,397] [    INFO] - The punc text: 我认为跑步最重要的就是给我带来了身体健康。
    [2022-05-09 18:19:04,397] [    INFO] - Response time 0.092407 s.
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_client import TextClientExecutor
    
    textclient_executor = TextClientExecutor()
    res = textclient_executor(
        input="我认为跑步最重要的就是给我带来了身体健康",
        server_ip="127.0.0.1",
        port=8090,)
    print(res)
    

    输出:

    我认为跑步最重要的就是给我带来了身体健康。
    

服务支持的模型

ASR 支持的模型

通过 paddlespeech_server stats --task asr 获取 ASR 服务支持的所有模型,其中静态模型可用于 paddle inference 推理。

TTS 支持的模型

通过 paddlespeech_server stats --task tts 获取 TTS 服务支持的所有模型,其中静态模型可用于 paddle inference 推理。

CLS 支持的模型

通过 paddlespeech_server stats --task cls 获取 CLS 服务支持的所有模型,其中静态模型可用于 paddle inference 推理。

Vector 支持的模型

通过 paddlespeech_server stats --task vector 获取 Vector 服务支持的所有模型。

Text支持的模型

通过 paddlespeech_server stats --task text 获取 Text 服务支持的所有模型。