使用 PyAudio、语音识别、pyttsx3 和 SerpApi 构建简单的基于 CLI 的语音助手

德米特里·祖布☀️

一、介绍

正如您从标题中看到的，这是一个演示项目，显示了一个非常基本的语音助手脚本，可以根据 Google 搜索结果在终端中回答您的问题。

您可以在 GitHub 存储库中找到完整代码：dimitryzub/serpapi-demo-projects/speech-recognition/cli-based/

后续博客文章将涉及：

使用Flask、一些 HTML、CSS 和 Javascript 的基于 Web 的解决方案。
使用Flutter和Dart的基于 Android 和 Windows 的解决方案。

二、我们将在这篇博文中构建什么

2.1 环境准备

首先，让我们确保我们处于不同的环境中，并正确安装项目所需的库。最难（可能）是安装 .pyaudio，关于此种困难可以参看下文克服：

[解决]修复 win 32/64 位操作系统上的 PyAudio pip 安装错误

2.2 虚拟环境和库安装

在开始安装库之前，我们需要为此项目创建并激活一个新环境：

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# if you're on Linux based systems
$ python -m venv env && source env/bin/activate
$ (env) <path>

# if you're on Windows and using Bash terminal
$ python -m venv env && source env/Scripts/activate
$ (env) <path>

# if you're on Windows and using CMD
python -m venv env && .\env\Scripts\activate
$ (env) <path>

解释python -m venv env告诉 Python 运行 module( -m)venv并创建一个名为的文件夹env。&&代表"与"。source <venv_name>/bin/activate将激活您的环境，并且您将只能在该环境中安装库。

现在安装所有需要的库：

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pip install rich pyttsx3 SpeechRecognition google-search-results

现在到pyaudio. 请记住，pyaudio安装时可能会引发错误。您可能需要进行额外的研究。

如果您使用的是 Linux，我们需要安装一些开发依赖项才能使用 pyaudio：

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$ sudo apt-get install -y libasound-dev portaudio19-dev
$ pip install pyaudio

如果您使用的是 Windows，则更简单（使用 CMD 和 Git Bash 进行测试）：

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pip install pyaudio

三、完整代码

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import os
import speech_recognition
import pyttsx3
from serpapi import GoogleSearch
from rich.console import Console
from dotenv import load_dotenv

load_dotenv('.env')
console = Console()

def main():
    console.rule('[bold yellow]SerpApi Voice Assistant Demo Project')
    recognizer = speech_recognition.Recognizer()

    while True:
        with console.status(status='Listening you...', spinner='point') as progress_bar:
            try:
                with speech_recognition.Microphone() as mic:
                    recognizer.adjust_for_ambient_noise(mic, duration=0.1)
                    audio = recognizer.listen(mic)
                    text = recognizer.recognize_google(audio_data=audio).lower()
                    console.print(f'[bold]Recognized text[/bold]: {text}')

                    progress_bar.update(status='Looking for answers...', spinner='line')
                    params = {
                        'api_key': os.getenv('API_KEY'),
                        'device': 'desktop',
                        'engine': 'google',
                        'q': text,
                        'google_domain': 'google.com',
                        'gl': 'us',
                        'hl': 'en'
                    }
                    search = GoogleSearch(params)
                    results = search.get_dict()

                    try:
                        if 'answer_box' in results:
                            try:
                                primary_answer = results['answer_box']['answer']
                            except:
                                primary_answer = results['answer_box']['result']
                            console.print(f'[bold]The answer is[/bold]: {primary_answer}')
                        elif 'knowledge_graph' in results:
                            secondary_answer = results['knowledge_graph']['description']
                            console.print(f'[bold]The answer is[/bold]: {secondary_answer}')
                        else:
                            tertiary_answer = results['answer_box']['list']
                            console.print(f'[bold]The answer is[/bold]: {tertiary_answer}')

                        progress_bar.stop() # if answered is success -> stop progress bar.
                        user_promnt_to_contiune_if_answer_is_success = input('Would you like to to search for something again? (y/n) ')

                        if user_promnt_to_contiune_if_answer_is_success == 'y':
                            recognizer = speech_recognition.Recognizer()
                            continue # run speech recognizion again until `user_promt` == 'n'
                        else:
                            console.rule('[bold yellow]Thank you for cheking SerpApi Voice Assistant Demo Project')
                            break
                    except KeyError:
                        progress_bar.stop()
                        error_user_promt = input("Sorry, didn't found the answer. Would you like to rephrase it? (y/n) ")

                        if error_user_promt == 'y':
                            recognizer = speech_recognition.Recognizer()
                            continue # run speech recognizion again until `user_promt` == 'n'
                        else:
                            console.rule('[bold yellow]Thank you for cheking SerpApi Voice Assistant Demo Project')
                            break
            except speech_recognition.UnknownValueError:
                progress_bar.stop()
                user_promt_to_continue = input('Sorry, not quite understood you. Could say it again? (y/n) ')

                if user_promt_to_continue == 'y':
                    recognizer = speech_recognition.Recognizer()
                    continue # run speech recognizion again until `user_promt` == 'n'
                else:
                    progress_bar.stop()
                    console.rule('[bold yellow]Thank you for cheking SerpApi Voice Assistant Demo Project')
                    break

if __name__ == '__main__':
    main()

四、代码说明

导入库：

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import os
import speech_recognition
import pyttsx3
from serpapi import GoogleSearch
from rich.console import Console
from dotenv import load_dotenv

rich用于在终端中进行漂亮格式化的 Python 库。
pyttsx3Python 的文本到语音转换器可离线工作。
SpeechRecognition用于将语音转换为文本的 Python 库。
google-search-resultsSerpApi 的 Python API 包装器，可解析来自 15 个以上搜索引擎的数据。
os读取秘密环境变量。在本例中，它是 SerpApi API 密钥。
dotenv从文件加载环境变量（SerpApi API 密钥）.env。.env文件可以重命名为任何文件：（.napoleon .点）代表环境变量文件。

定义rich Console(). 它将用于美化终端输出（动画等）：

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console = Console()

定义main所有发生的函数：

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def main():
    console.rule('[bold yellow]SerpApi Voice Assistant Demo Project')
    recognizer = speech_recognition.Recognizer()

在函数的开头，我们定义speech_recognition.Recognizer()并将console.rule创建以下输出：

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───────────────────────────────────── SerpApi Voice Assistant Demo Project ─────────────────────────────────────

下一步是创建一个 while 循环，该循环将不断监听麦克风输入以识别语音：

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while True:
    with console.status(status='Listening you...', spinner='point') as progress_bar:
        try:
            with speech_recognition.Microphone() as mic:
                recognizer.adjust_for_ambient_noise(mic, duration=0.1)
                audio = recognizer.listen(mic)

                text = recognizer.recognize_google(audio_data=audio).lower()
                console.print(f'[bold]Recognized text[/bold]: {text}')

console.status-rich进度条，仅用于装饰目的。
speech_recognition.Microphone()开始从麦克风拾取输入。
recognizer.adjust_for_ambient_noise旨在根据环境能量水平校准能量阈值。
recognizer.listen监听实际的用户文本。
recognizer.recognize_google使用 Google Speech Recongition API 执行语音识别。lower()是降低识别文本。
console.print允许使用文本修改的语句rich print，例如添加粗体、斜体等。

spinner='point'将产生以下输出（使用 python -m rich.spinner 查看列表 spinners）：

之后，我们需要初始化 SerpApi 搜索参数以进行搜索：

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progress_bar.update(status='Looking for answers...', spinner='line') 
params = {
    'api_key': os.getenv('API_KEY'),  # serpapi api key   
    'device': 'desktop',              # device used for 
    'engine': 'google',               # serpapi parsing engine: https://serpapi.com/status
    'q': text,                        # search query 
    'google_domain': 'google.com',    # google domain:          https://serpapi.com/google-domains
    'gl': 'us',                       # country of the search:  https://serpapi.com/google-countries
    'hl': 'en'                        # language of the search: https://serpapi.com/google-languages
    # other parameters such as locations: https://serpapi.com/locations-api
}
search = GoogleSearch(params)         # where data extraction happens on the SerpApi backend
results = search.get_dict()           # JSON -> Python dict

progress_bar.update将会progress_bar用新的status（控制台中打印的文本）进行更新，spinner='line'并将产生以下动画：

之后，使用 SerpApi 的Google 搜索引擎 API从 Google 搜索中提取数据。

代码的以下部分将执行以下操作：

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try:
    if 'answer_box' in results:
        try:
            primary_answer = results['answer_box']['answer']
        except:
            primary_answer = results['answer_box']['result']
        console.print(f'[bold]The answer is[/bold]: {primary_answer}')

     elif 'knowledge_graph' in results:
            secondary_answer = results['knowledge_graph']['description']
            console.print(f'[bold]The answer is[/bold]: {secondary_answer}')
        else:
            tertiary_answer = results['answer_box']['list']
            console.print(f'[bold]The answer is[/bold]: {tertiary_answer}')
        progress_bar.stop()  # if answered is success -> stop progress bar

        user_promnt_to_contiune_if_answer_is_success = input('Would you like to to search for something again? (y/n) ')

        if user_promnt_to_contiune_if_answer_is_success == 'y':
            recognizer = speech_recognition.Recognizer()
            continue         # run speech recognizion again until `user_promt` == 'n'
        else:
            console.rule('[bold yellow]Thank you for cheking SerpApi Voice Assistant Demo Project')
            break

    except KeyError:
        progress_bar.stop()  # if didn't found the answer -> stop progress bar
        error_user_promt = input("Sorry, didn't found the answer. Would you like to rephrase it? (y/n) ")

        if error_user_promt == 'y':
            recognizer = speech_recognition.Recognizer()
            continue         # run speech recognizion again until `user_promt` == 'n'
        else:
            console.rule('[bold yellow]Thank you for cheking SerpApi Voice Assistant Demo Project')
            break

最后一步是处理麦克风没有拾取声音时的错误：

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# while True:
#     with console.status(status='Listening you...', spinner='point') as progress_bar:
#         try:
            # speech recognition code
            # data extraction code
        except speech_recognition.UnknownValueError:
                progress_bar.stop()         # if didn't heard the speech -> stop progress bar
                user_promt_to_continue = input('Sorry, not quite understood you. Could say it again? (y/n) ')

          if user_promt_to_continue == 'y':
              recognizer = speech_recognition.Recognizer()
              continue               # run speech recognizion again until `user_promt` == 'n'
          else:
              progress_bar.stop()    # if want to quit -> stop progress bar
              console.rule('[bold yellow]Thank you for cheking SerpApi Voice Assistant Demo Project')
              break

console.rule()将提供以下输出：

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───────────────────── Thank you for cheking SerpApi Voice Assistant Demo Project ──────────────────────

添加if __name__ == '__main__'惯用语，以防止用户在无意时意外调用某些脚本，并调用main将运行整个脚本的函数：

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if __name__ == '__main__':
    main()

使用 PyAudio、语音识别、pyttsx3 和 SerpApi 构建简单的基于 CLI 的语音助手

一、介绍

二、我们将在这篇博文中构建什么

2.1 环境准备

2.2 虚拟环境和库安装

三、完整代码

四、代码说明

五、链接