main
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111dfaf20d
commit
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import tkinter as tk
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import threading
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import speech_recognition as sr
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import requests
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import pyttsx3
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from AiChatterbot import talkWithRobot, robotSay
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# Initialize speech synthesis object
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talker = pyttsx3.init()
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# Initialize speech recognition object
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recognizer = sr.Recognizer()
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userName = "admin"
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userPass = "123"
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# Create chat window
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def chat_window():
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chat_window = tk.Tk()
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chat_window.title("对话")
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chat_window.geometry("800x400")
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def send_text_message():
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message = input_entry.get()
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chat_text.insert(tk.END, "你: " + message + "\n")
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response = get_response(message)
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chat_text.insert(tk.END, "机器人: " + response + "\n")
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input_entry.delete(0, tk.END)
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# 语音合成回复并播放
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talker.say(response)
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talker.runAndWait()
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def start_voice_recognition(chat_text):
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with sr.Microphone() as source:
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print("请说话...")
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audio = recognizer.listen(source)
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try:
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print("识别中...")
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text = recognizer.recognize_google(audio, language="zh-CN")
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print("你说: " + text)
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# 调用自然语言处理功能获取回复
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response = get_response(text)
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# 显示用户输入的消息和机器人的回复
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chat_text.insert(tk.END, "你: " + text + "\n")
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chat_text.insert(tk.END, "机器人: " + response + "\n")
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# 语音合成回复并播放
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talker.say(response)
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talker.runAndWait()
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except sr.UnknownValueError:
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print("抱歉, 未能识别，请重试")
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def send_voice_message():
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start_voice_recognition(chat_text)
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chat_frame = tk.Frame(chat_window)
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chat_frame.pack(pady=10)
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chat_text = tk.Text(chat_frame)
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chat_text.pack()
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input_entry = tk.Entry(chat_frame)
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input_entry.pack(side=tk.LEFT, expand=True, fill=tk.BOTH)
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send_text_button = tk.Button(chat_frame, text="发送", command=send_text_message)
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send_text_button.pack(side=tk.LEFT)
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send_voice_button = tk.Button(chat_frame, text="语音输入", command=start_voice_recognition)
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send_voice_button.pack(side=tk.LEFT)
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chat_window.mainloop()
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# 启动聊天窗口
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# 创建登录窗口
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def login_window():
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login_window = tk.Tk()
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login_window.title("登录")
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# 获取屏幕宽度和高度
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screen_width = login_window.winfo_screenwidth()
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screen_height = login_window.winfo_screenheight()
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# 设置窗口居中
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window_width = 300
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window_height = 200
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x = (screen_width - window_width) // 2
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y = (screen_height - window_height) // 2
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login_window.geometry(f"{window_width}x{window_height}+{x}+{y}")
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def login():
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inputName = name_entry.get()
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inputPass = pass_entry.get()
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if inputName == userName and inputPass == userPass:
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talker.say("恭喜你登录成功！")
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talker.runAndWait()
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login_window.destroy()
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chat_window()
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else:
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talker.say("账号或密码错误，登录失败")
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talker.runAndWait()
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name_label = tk.Label(login_window, text="用户名:")
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name_label.pack()
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name_entry = tk.Entry(login_window)
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name_entry.pack()
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pass_label = tk.Label(login_window, text="密码:")
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pass_label.pack()
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pass_entry = tk.Entry(login_window, show="*")
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pass_entry.pack()
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login_button = tk.Button(login_window, text="登录", command=login)
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login_button.pack()
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login_window.mainloop()
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# 自然语言处理功能
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def get_response(message):
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if "你好" in message:
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return "你好，有什么可以帮助你的吗？"
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elif "再见" in message:
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return "再见，祝你一天愉快！"
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else:
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return "抱歉，我不明白你说的是什么。"
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def send_message():
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# 获取用户输入的消息
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chat_text = tk.Text(chat_window)
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chat_text.pack()
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input_entry = tk.Entry(chat_window)
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input_entry.pack()
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message = input_entry.get()
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# 显示用户输入的消息
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chat_text.insert(tk.END, "You: " + message + "\n")
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# 获取模型生成的回复
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response = get_response(message)
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# 显示模型生成的回复
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chat_text.insert(tk.END, "Bot: " + response + "\n")
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# 启动登录窗口
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login_window()
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@ -0,0 +1,184 @@
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import time
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import wave
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import requests
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from pyaudio import PyAudio, paInt16
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from aip import AipSpeech
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import pyttsx3
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from tkinter import *
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from tkinter import messagebox
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import speech_recognition as sr
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import nltk
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from nltk.tokenize import word_tokenize
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from nltk.corpus import stopwords
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from nltk.tokenize import RegexpTokenizer
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from nltk.stem import WordNetLemmatizer
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from nltk.probability import FreqDist
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import string
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# Constants for audio recording
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framer = 16000 # Sample rate
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num_samples = 2000 # Sample points
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channels = 1
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sampwidth = 2
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FILEPATH = 'myvoices.wav' # Specify the path to save the recorded audio file
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APP_ID = '73927317'
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API_KEY = '3jGcj5fLma64CtB3tTEuLcei'
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SECRET_KEY = 'qm8gPCF7DSKpqatx5ZQ8e4OvNLmgdYcG' # Add your own API credentials here
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# Class for handling audio recording and saving
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class Speak():
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def save_wave_file(self, filepath, data):
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wf = wave.open(filepath, 'wb')
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wf.setnchannels(channels)
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wf.setsampwidth(sampwidth)
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wf.setframerate(framer)
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wf.writeframes(b''.join(data))
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wf.close()
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def my_record(self):
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pa = PyAudio()
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stream = pa.open(format=paInt16, channels=channels, rate=framer, input=True, frames_per_buffer=num_samples)
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my_buf = [] # Store recorded data
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t_end = time.time() + 5 # Record for 5 seconds
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print('Speak now...')
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while time.time() < t_end:
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string_audio_data = stream.read(num_samples)
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my_buf.append(string_audio_data)
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print('Recording ended')
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self.save_wave_file(FILEPATH, my_buf) # Save the recorded audio
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stream.close()
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# Initialize the AipSpeech client
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client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
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# Class for handling text-to-speech
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class RobotSay():
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def __init__(self):
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self.engine = pyttsx3.init() # Initialize TTS engine
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def say(self, msg):
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self.engine.say(msg)
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self.engine.runAndWait()
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# Class for handling speech recognition
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class ReadWav():
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def get_file_content(self, filePath):
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with open(filePath, 'rb') as fp:
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return fp.read()
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def predict(self):
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return client.asr(self.get_file_content('myvoices.wav'), 'wav', 16000, {
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'dev_pid': 1537,
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})
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# Define the login window
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class LoginWindow:
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def __init__(self, master):
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self.master = master
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self.master.title("登录")
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self.master.geometry("300x200")
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# Center align the login window
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self.screen_width = self.master.winfo_screenwidth()
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self.screen_height = self.master.winfo_screenheight()
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self.x_pos = (self.screen_width - 300) // 2
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self.y_pos = (self.screen_height - 200) // 2
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self.master.geometry(f"300x200+{self.x_pos}+{self.y_pos}")
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self.label_username = Label(master, text="账号")
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self.label_username.pack()
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self.entry_username = Entry(master)
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self.entry_username.pack()
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self.label_password = Label(master, text="密码")
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self.label_password.pack()
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self.entry_password = Entry(master, show="*")
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self.entry_password.pack()
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self.button_login = Button(master, text="登录", command=self.login)
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self.button_login.pack()
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def login(self):
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username = self.entry_username.get()
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password = self.entry_password.get()
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# You can add actual validation logic here by checking against a database or hardcoded values
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if username == "123" and password == "123":
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messagebox.showinfo("登陆成功", "恭喜你登陆成功")
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self.open_chat_window()
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else:
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messagebox.showerror("登录失败", "无效的用户名或密码")
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def open_chat_window(self):
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self.master.withdraw() # Hide the login window
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chat_root = Toplevel(self.master) # Create a new window for chat
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chat_window = ChatWindow(chat_root) # Open the chat window
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chat_root.protocol("WM_DELETE_WINDOW", self.master.quit) # Close the entire application when chat window is closed
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class ChatWindow:
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def __init__(self, master):
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self.master = master
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self.master.title("开始聊天")
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self.master.geometry("700x500")
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self.chat_text = Text(self.master)
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self.chat_text.pack()
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self.input_field = Entry(self.master)
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self.input_field.pack()
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self.send_button = Button(self.master, text="发送", command=self.send_message)
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self.send_button.pack()
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self.recognizer = sr.Recognizer()
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self.engine = pyttsx3.init()
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def send_message(self):
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user_input = self.input_field.get()
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self.update_chat("你: " + user_input + "\n")
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response = self.get_qingyunke_response(user_input)
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self.update_chat("菲菲: " + response + "\n")
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self.speak(response) # Speaking the response
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def get_qingyunke_response(self, message):
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api_url = "http://api.qingyunke.com/api.php?key=free&appid=0&msg=" + message
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response = requests.get(api_url)
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if response.status_code == 200:
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data = response.json()
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if data['result'] == 0:
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return data['content']
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else:
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return "对不起，我不能理解."
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else:
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return "我目前无法处理您的请求."
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# 下载NLTK数据
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nltk.download('stopwords')
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nltk.download('punkt')
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nltk.download('wordnet')
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# 假设用户输入作为文本样本
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user_input = "我想了解自然语言处理。你能帮助我吗？"
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# 小写化
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user_input = user_input.lower()
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# 标点符号移除
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translator = str.maketrans('', '', string.punctuation)
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user_input = user_input.translate(translator)
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# 分词
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tokens = word_tokenize(user_input)
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# 去除停用词
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stop_words = set(stopwords.words('english'))
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filtered_tokens = [word for word in tokens if word not in stop_words]
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# 词形还原
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lemmatizer = WordNetLemmatizer()
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lemmatized_tokens = [lemmatizer.lemmatize(word) for word in filtered_tokens]
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# 频率分布
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fdist = FreqDist(lemmatized_tokens)
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print(fdist.most_common(5))
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def update_chat(self, text):
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self.chat_text.insert(END, text)
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def speak(self, text):
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self.engine.say(text)
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self.engine.runAndWait()
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def main():
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root = Tk()
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login_window = LoginWindow(root)
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root.mainloop()
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if __name__ == "__main__":
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main()
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