口語人機交互 Spoken Human Robot Interaction

• 一、交互結構總覽
• 二、展示
• • 一、代碼背景
  • 二、對話運行結果展示
  • • 對話一
    • 對話二
    • 對話三
    • 對話四
• 三、實現代碼

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如何制作一個低配山寨版賈維斯?

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一、交互結構總覽

• 第一步：首先通過語音輸入設備，將語音信息輸入計算機。這里我使用speech_recognition.sr.Microphone() 函數調用計算機麥克風，然后 sr.Recognizer().listen() 將麥克風輸入的語音信息保留下來。

• 第二步：使用語言識別庫，將輸入語音信息轉為文本信息。sr.Recognizer().recognize_google() 使用谷歌的語音識別獲取文本信息。

• 第三步：使用 en_core_web_sm 庫對語言進行解析，并繪制依賴樹

• 第四步： 根據文本單詞的詞性或者特定詞（此處可以自由替換對話中的某些信息，比如時間，數量等，并讓計算機可以識別到這些信息），來讓計算機自動回復設定好的語音（用Espeak工具可以讓計算機用語音讀出文本）

二、展示

一、代碼背景

我設定的對話背景是，我的計算機是個低配版賈維斯 (是真的低配) ，他管理我的房子，然后有朋友要來家里做客，我讓賈維斯幫我提前做一些準備。

二、對話運行結果展示

為了方便，所用的包均用的英文，讀者可以自由替換語言包，比如中文包

對話一

賈維斯：What can I do for you sir? 我： today my friends will come to my house

下面的對話可以是任意人數，賈維斯會識別語言中的表示數字的單詞，并在后面的對話中復述出來。

賈維斯：Sir, How many friends will come? 我： maybe six people

對話二

這里“ isyncr” 其實是 “I think”，谷歌語音識別的不是特別準（當然不能是我發音不漂準！）

此處語音可選擇 三種飲料中的一種，賈維斯識別后會復述一遍你的選擇

賈維斯：and what drinks do I need to prepare？cola, tea or coffee? 我 ： isyncr coffee is the best 賈維斯：got it sir, I will prepare six cups of coffe

對話三

賈維斯：By the way, sir, when they will come? 我： if I remember correctly live well, either 5 p.m. 賈維斯：Sir, please confirm, your six friends will come at 5. pm and I will prepare six cups of coffe for them

對話四

賈維斯：And Sir, your house looks not clean, can I clean it now? 我：yes of course please 賈維斯：As your wish, please wait a moment 賈維斯：Sir, your house is clean now! 賈維斯：Have a nice day sir!

三、實現代碼

我還在開頭加了個下載好的賈維斯“歡迎回家”的語音包，代碼及語音包戳這里

import speech_recognition as sr import en_core_web_sm import os import spacy from spacy import displacy from spacy.symbols import NOUN, NUM, VERB from nltk import Tree import winsound# Built a nltk tree def to_nltk_tree(node):if node.n_lefts + node.n_rights > 0:return Tree(node.orth_, [to_nltk_tree(child) for child in node.children])else:return node.orth_def dependency_tree(text):nlp = en_core_web_sm.load()nlp_doc = nlp(text)print('---------------')print('Dependency Graph')[to_nltk_tree(sent.root).pretty_print() for sent in nlp_doc.sents]print('---------------')def clean():winsound.PlaySound('Jarvis/Jarvis-System/Garbage cleared.wav', winsound.SND_FILENAME)reply = 'Sir, your house is clean now!'print(reply)os.system('espeak "{}"'.format(reply))winsound.PlaySound('Jarvis/Jarvis-System/Welcome Home Sir(No Song).wav', winsound.SND_FILENAME)#today my friends will come to my house r = sr.Recognizer() with sr.Microphone() as source:l = "What can I do for you sir?"print(l)os.system('espeak "{}"'.format(l))audio = r.listen(source)try:textT = r.recognize_google(audio) except sr.UnknownValueError:print("Jarvis could not understand your audio") except sr.RequestError as e:print("Could not request results from Google Speech Recognition service; {0}".format(e))print(textT) dependency_tree(textT)nlp = en_core_web_sm.load() nlp_doc = nlp(textT)for word in nlp_doc:if word.pos == VERB and str(word) == 'come':l = 'Sir, How many friends will come?'print(l)os.system('espeak "{}"'.format(l))with sr.Microphone() as source:audio = r.listen(source)try:textT = r.recognize_google(audio)except sr.UnknownValueError:print("Jarvis could not understand your audio")except sr.RequestError as e:print("Could not request results from Google Speech Recognition service; {0}".format(e))print(textT)dependency_tree(textT)nlp = en_core_web_sm.load()nlp_doc = nlp(textT)for word in nlp_doc:if word.pos == NUM:friends_num = str(word) #I remember six people# I think tea is the best r = sr.Recognizer() with sr.Microphone() as source:l = "and what drinks do I need to prepare？cola, tea or coffee?"print(l)os.system('espeak "{}"'.format(l))audio = r.listen(source)try:textT = r.recognize_google(audio) except sr.UnknownValueError:print("Jarvis could not understand your audio") except sr.RequestError as e:print("Could not request results from Google Speech Recognition service; {0}".format(e))print(textT) dependency_tree(textT)if 'tea' in textT.lower():drink = 'tea'l = 'got it sir, I will prepare ' + friends_num+' cups of tea' elif 'cola' in textT.lower():drink = 'cola'l = 'got it sir, I will prepare ' + friends_num+' cups of cola' elif 'coffe' in textT.lower():drink = 'coffe'l = 'got it sir, I will prepare ' + friends_num+' cups of coffe' else:l0 = 'Sir, can you please say it again?'print(l0)os.system('espeak "{}"'.format(l0))print(l) os.system('espeak "{}"'.format(l))#If I remeber correctly, they will come at 5 pm r = sr.Recognizer() with sr.Microphone() as source:l = "By the way, sir, when they will come?"print(l)os.system('espeak "{}"'.format(l))audio = r.listen(source)try:textT = r.recognize_google(audio) except sr.UnknownValueError:print("Jarvis could not understand your audio") except sr.RequestError as e:print("Could not request results from Google Speech Recognition service; {0}".format(e))print(textT) dependency_tree(textT) nlp_doc = nlp(textT)time_num = ''for word in nlp_doc:if word.pos == NUM:time_num += str(word) + '.'if 'a.m.' in textT.lower():m = 'am'elif 'p.m.' in textT.lower():m = 'pm'else:m = 'pm'l = 'Sir, please confirm, your ' + friends_num + ' friends will come at '\+ time_num + ' ' + m + ' and I will prepare ' + friends_num + ' cups of ' + drink + ' for them' print(l) os.system('espeak "{}"'.format(l))r = sr.Recognizer() with sr.Microphone() as source:l = "And Sir, your house looks not clean, can I clean it now?"print(l)os.system('espeak "{}"'.format(l))audio = r.listen(source)try:textT = r.recognize_google(audio) except sr.UnknownValueError:print("Jarvis could not understand your audio") except sr.RequestError as e:print("Could not request results from Google Speech Recognition service; {0}".format(e))print(textT) dependency_tree(textT) if 'yes' or 'yeah' in textT.lower():l = 'As your wish, please wait a moment'print(l)os.system('espeak "{}"'.format(l))clean()l = 'Have a nice day sir!'print(l)os.system('espeak "{}"'.format(l))

當然，讀者可以在此框架下，加入RNN來讓賈維斯的回復更加智能！

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