春色將闌，鶯聲漸老，紅英落盡青梅小。畫堂人靜雨蒙蒙，屏山半掩余香裊。
密約沉沉，離情杳杳，菱花塵滿慵將照。倚樓無語欲銷魂，長空黯淡連芳草。

首先安裝python包

pip3 install baidu-aip

再注冊百度AI得到相關參數

https://ai.baidu.com/

一、語音合成

from aip import AipSpeechAPP_ID = '14446020' API_KEY = 'GnaoLWrIiTKP10disiDHMiNZ' SECRET_KEY = 'FYaMNBsH5NFsgWcRsyBfaHDV70MvvE6u'#實例化AipSpeech對象 client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)#調用方法語音合成 result = client.synthesis("歡迎來到王者榮耀",options={"per": 1,"spd": 9,"pit": 9,"vol": 15,}) if not isinstance(result, dict):with open('auido.mp3', 'wb') as f:f.write(result)

二、語音識別

from aip import AipSpeech import osAPP_ID = '14446020' API_KEY = 'GnaoLWrIiTKP10disiDHMiNZ' SECRET_KEY = 'FYaMNBsH5NFsgWcRsyBfaHDV70MvvE6u'client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)def get_file_content(filePath):cmd_str = f"ffmpeg -y -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath}.pcm"os.system(cmd_str)with open(f"{filePath}.pcm", 'rb') as fp:return fp.read()res = client.asr(speech=get_file_content("auido.mp3"),options={"dev_pid":1536, })print(res["result"][0])

這里用到一個格式轉換的軟件，百度地址：
https://pan.baidu.com/s/1MadxSh-A0Pzo1Su_wKdktQ 提取碼：x5xi
固定的格式轉換命令：（需要將bin文件添加環境變量，在cmd中執行）
ffmpeg -y -i filePath -acodec pcm_s16le -f s16le -ac 1 -ar 16000 filePath.pcm

三、短文本相似度

from aip import AipNlpAPP_ID = '14446020' API_KEY = 'GnaoLWrIiTKP10disiDHMiNZ' SECRET_KEY = 'FYaMNBsH5NFsgWcRsyBfaHDV70MvvE6u' client = AipNlp(APP_ID,API_KEY,SECRET_KEY)ret = client.simnet("你今年幾歲了？","多大年齡了？") print(ret)

{'log_id': 4545309161914786697, 'texts': {'text_2': '多大年齡了？', 'text_1': '你今年幾歲了？'}, 'score': 0.742316} score 是兩個測試的短文本相似度，一般大于0.72的兩個短文本的意思是相似的句子！

四、代碼實現對接圖靈

import requestsdef tuling_test(question):url = "http://openapi.tuling123.com/openapi/api/v2"data = {"reqType":0,"perception": {"inputText": {"text": question},"inputImage": {},},"userInfo": {"apiKey": "2f4e809b8b3049ce82a6b4787bad65bb","userId": "wangjifei"}}return requests.post(url=url,json=data).json()ret = tuling_test("心情不好") print(ret.get("results")[0]["values"]["text"])

五、簡單實現人機交流

• 基本步驟：
  用戶錄制音頻---傳入函數---格式轉化---語音識別---匹配答案---語音合成---語音文件流寫入文件---os執行文件---刪除文件

from aip import AipSpeech from aip import AipNlp from uuid import uuid4 import os import requests import timeAPP_ID = '14446007' API_KEY = 'QrQWLLg5a8qld7Qty7avqCGC' SECRET_KEY = 'O5mE31LSl17hm8NRYyf9PwlE5Byqm0nr'client = AipSpeech(APP_ID, API_KEY, SECRET_KEY) nlp_client = AipNlp(APP_ID, API_KEY, SECRET_KEY)def tuling_test(question):"""接入圖靈，為問題匹配答案"""url = "http://openapi.tuling123.com/openapi/api/v2"data = {"reqType": 0,"perception": {"inputText": {"text": question},"inputImage": {},},"userInfo": {"apiKey": "2f4e809b8b3049ce82a6b4787bad65bb","userId": "wangjifei"}}ret = requests.post(url=url, json=data).json()return ret.get("results")[0]["values"]["text"]def get_file_content(filePath):"""音頻的格式轉換"""cmd_str = f"ffmpeg -y -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath}.pcm"os.system(cmd_str)with open(f"{filePath}.pcm", 'rb') as fp:return fp.read()def custom_reply(text):"""根據問題得到相應的答案，可以通過短文本相似來自定義，也可以調用圖靈問題庫"""if nlp_client.simnet("你叫什么名字", text).get("score") >= 0.72:return "我不能告訴你"return tuling_test(text)def learn_say(file_name):"""機器人學說話"""# 語音識別成文字res = client.asr(speech=get_file_content(file_name), options={"dev_pid": 1536,})os.remove(f"{file_name}.pcm")text = res.get("result")[0]# 根據問題得到相關答案text1 = custom_reply(text)# 答案語音合成res_audio = client.synthesis(text1, options={"vol": 8,"pit": 8,"spd": 5,"per": 4})# 通過uuid 生成文件名ret_file_name = f"{uuid4()}.mp3"# 將生成的語音流寫入文件中with open(ret_file_name, "wb") as f:f.write(res_audio)# 執行音頻文件ret = os.system(ret_file_name)time.sleep(2)os.remove(ret_file_name)if __name__ == '__main__':learn_say("auido.m4a")

六、網頁版智能機器人對話

flask_ws.py

from flask import Flask, request, render_template from uuid import uuid4 from geventwebsocket.websocket import WebSocket from gevent.pywsgi import WSGIServer from geventwebsocket.handler import WebSocketHandler from learn_say import learn_sayapp = Flask(__name__) # type:Flask@app.route("/ws") def ws():user_socket = request.environ.get("wsgi.websocket") # type:WebSocketwhile True:msg = user_socket.receive()q_file_name = f"{uuid4()}.wav"with open(q_file_name, "wb") as f:f.write(msg)ret_file_name = learn_say(q_file_name)user_socket.send(ret_file_name)if __name__ == '__main__':http_serv = WSGIServer(("127.0.0.1", 8006), app, handler_class=WebSocketHandler)http_serv.serve_forever()

flask_app.py

from flask import Flask, request, render_template, send_fileapp = Flask(__name__) # type:Flask@app.route("/index") def index():return render_template("index.html")@app.route("/get_audio/<audio_name>") def get_audio(audio_name):return send_file(audio_name)if __name__ == '__main__':app.run("127.0.0.1", 8008, debug=True)

learn_say.py

from aip import AipSpeech from aip import AipNlp from uuid import uuid4 import os import requests import timeAPP_ID = '14446007' API_KEY = 'QrQWLLg5a8qld7Qty7avqCGC' SECRET_KEY = 'O5mE31LSl17hm8NRYyf9PwlE5Byqm0nr'client = AipSpeech(APP_ID, API_KEY, SECRET_KEY) nlp_client = AipNlp(APP_ID, API_KEY, SECRET_KEY)def tuling_test(question):"""接入圖靈，為問題匹配答案"""url = "http://openapi.tuling123.com/openapi/api/v2"data = {"reqType": 0,"perception": {"inputText": {"text": question},"inputImage": {},},"userInfo": {"apiKey": "2f4e809b8b3049ce82a6b4787bad65bb","userId": "wangjifei"}}ret = requests.post(url=url, json=data).json()return ret.get("results")[0]["values"]["text"]def get_file_content(filePath):"""音頻的格式轉換"""cmd_str = f"ffmpeg -y -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath}.pcm"os.system(cmd_str)with open(f"{filePath}.pcm", 'rb') as fp:return fp.read()def custom_reply(text):"""根據問題得到相應的答案，可以通過短文本相似來自定義，也可以調用圖靈問題庫"""if nlp_client.simnet("你叫什么名字", text).get("score") >= 0.72:return "我不能告訴你"return tuling_test(text)def learn_say(file_name):"""機器人學說話"""# 語音識別成文字res = client.asr(speech=get_file_content(file_name), options={"dev_pid": 1536,})os.remove(file_name)os.remove(f"{file_name}.pcm")text = res.get("result")[0]# 根據問題得到相關答案text1 = custom_reply(text)# 答案語音合成res_audio = client.synthesis(text1, options={"vol": 8,"pit": 8,"spd": 5,"per": 4})# 通過uuid 生成文件名ret_file_name = f"{uuid4()}.mp3"# 將生成的語音流寫入文件中with open(ret_file_name, "wb") as f:f.write(res_audio)return ret_file_name

index.html

<!DOCTYPE html> <html lang="en"> <head><meta charset="UTF-8"><title>Title</title></head> <body> <audio src="" autoplay controls id="player"></audio><button onclick="start_reco()">錄制消息</button> <br> <button onclick="stop_reco()">發送語音消息</button></body> <script src="/static/Recorder.js"></script> <script type="application/javascript">var serv = "http://127.0.0.1:8008";var ws_serv = "ws://127.0.0.1:8006/ws";var get_music = serv + "/get_audio/";var ws = new WebSocket(ws_serv);ws.onmessage = function (data) {document.getElementById("player").src = get_music + data.data};var reco = null;var audio_context = new AudioContext();navigator.getUserMedia = (navigator.getUserMedia ||navigator.webkitGetUserMedia ||navigator.mozGetUserMedia ||navigator.msGetUserMedia);navigator.getUserMedia({audio: true}, create_stream, function (err) {console.log(err)});function create_stream(user_media) {var stream_input = audio_context.createMediaStreamSource(user_media);reco = new Recorder(stream_input);}//錄制消息function start_reco() {reco.record();}//先停止錄制，再獲取音頻function stop_reco() {reco.stop();get_audio();reco.clear();}//獲取音頻，發送音頻function get_audio() {reco.exportWAV(function (wav_file) {// wav_file = Blob對象ws.send(wav_file);})} </script> </html>

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