构建智能化Linux语音交互系统 迈向人机对话新时代
随着信息技术的飞速发展，人机交互成为现代生活不可或缺的一部分。语音技术作为更直观、便捷的交互方式，逐渐成为人们关注的焦点。本文将展示如何利用Linux系统搭建一套智能语音识别与语音合成系统，为用户提供高效便捷的人机交互体验。
一、系统整体架构
这套系统基于Linux平台构建，采用Python语言开发。系统包含两大功能模块：语音识别模块和语音合成模块。语音识别模块借助一万网络的语音识别API，把用户的语音输入转化为文字信息；语音合成模块则通过一万网络的语音合成API，将系统生成的文字内容转化为语音输出。用户只需通过麦克风输入语音指令，系统即可自动识别并执行相应任务，同时以语音形式反馈操作结果。
二、语音识别模块实现细节
在语音识别模块的设计中，我们选择了一万网络提供的语音识别API。得益于一万网络Python SDK的支持，我们可以方便快捷地调用相关接口。首先，需要在一万网络开放平台注册账号，获取API Key和Secret Key，并完成SDK的安装配置。随后，利用PyAudio库录制用户的语音输入，将采集到的音频文件转换成PCM格式。最后，将处理好的PCM格式音频上传至一万网络服务器，获取最终的识别结果。以下是语音识别模块的核心代码示例：
“`python
import urllib.parse
import hmac
import hashlib
import base64
from aip import AipSpeech
import pyaudio
import wave
APP_ID = ‘YOUR_APP_ID’
API_KEY = ‘YOUR_API_KEY’
SECRET_KEY = ‘YOUR_SECRET_KEY’
def generate_request_param:
rate = 16000
format = ‘pcm’
channel = 1
cuid = ‘123456PYTHON’
dev_pid = 1537
param = {
‘dev_pid’: dev_pid,
‘cuid’: cuid,
‘rate’: rate,
‘channel’: channel,
‘format’: format
}
return param
def generate_request_url:
url = ”
grant_type = ‘client_credentials’
client_id = API_KEY
client_secret = SECRET_KEY
request_url = url + ‘?grant_type=’ + grant_type + ‘&client_id=’ + client_id + ‘&client_secret=’ + client_secret
return request_url
def get_token:
request_url = generate_request_url
token_response = urllib.request.urlopenrequest_url.read
token_content = json.loadstoken_response.decode’utf-8′
return token_content’access_token’
def get_file_contentfilepath:
with openfilepath, ‘rb’ as fp:
return fp.read
def recognize:
CHUNK = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 1
RATE = 16000
RECORD_SECONDS = 5
WAVE_OUTPUT_FILENAME = “output.wav”
p = pyaudio.PyAudio
stream = p.openformat=FORMAT, channels=CHANNELS, rate=RATE, input=True, frames_per_buffer=CHUNK
print”* recording”
frames =
for i in range0, intRATE / CHUNK * RECORD_SECONDS:
data = stream.readCHUNK
frames.appenddata
print”* done recording”
stream.stop_stream
stream.close
p.terminate
wf = wave.openWAVE_OUTPUT_FILENAME, ‘wb’
wf.setnchannelsCHANNELS
wf.setsampwidthp.get_sample_sizeFORMAT
wf.setframerateRATE
wf.writeframesb”.joinframes
wf.close
token = get_token
request_url = ” + ‘?access_token=’ + token
audio_data = get_file_contentWAVE_OUTPUT_FILENAME
params = generate_request_param
headers = {
‘Content-Type’: ‘audio/’ + params’format’ + ‘; rate=’ + strparams’rate’,
‘Content-Length’: lenaudio_data
}
signature_headers = headers.copy
signature_headers’Host’ = ‘vop.baidu.com’
signature_rs =
for key, value in signature_headers.items:
signature_rs.appendkey + ‘: ‘ + value
signature = ‘\n’.joinsignature_rs
http_method = ‘POST’
canonical_uri = ‘/server_api’
canonical_querystring = ”
canonical_headers = ‘Host:vop.baidu.com\n’ + signature
canonical_request = http_method + ‘\n’ \
+ canonical_uri + ‘\n’ \
+ canonical_querystring + ‘\n’ \
+ canonical_headers + ‘\n\n’ \
+ hashlib.md5audio_data.hexdigest
secret_key_bytes = bytesSECRET_KEY, encoding=’utf-8′
signature_bytes = bytessignature, encoding=’utf-8′
hmac_obj = hmac.newsecret_key_bytes, signature_bytes, hashlib.sha1
hmac_str = base64.b64encodehmac_obj.digest.decode’utf-8′
authorization_rs =
authorization_rs.append’bce-auth-v1′ + ‘/’ + API_KEY + ‘/’ + ‘2020-05-20T20:40:00Z’ + ‘/’ + ‘1800’ + ‘/’ + signature
authorization_rs.append’host:’ + ‘vop.baidu.com’
authorization_rs.append’x-bce-date:2020-05-20T20:40:00Z’
authorization_rs.append’x-bce-content-sha256:’ + hashlib.sha256audio_data.hexdigest
authorization = ‘\n’.joinauthorization_rs
headers’Authorization’ = authorization
response = requests.postrequest_url, headers=headers, data=audio_data
return response.json’result’0
“`
三、语音合成模块实现细节
语音合成模块同样基于一万网络的语音合成API展开设计。操作流程与语音识别模块类似，首先在一万网络开放平台获取API Key和Secret Key，安装必要的Python SDK。之后，将需要合成的文本内容通过API传输至一万网络服务器，服务器处理后返回一个PCM格式的音频文件，将其保存为WAV文件，最后通过PyAudio库播放音频。以下是语音合成模块的代码示例：
“`python
per = 0
spd = 5
pit = 5
vol = 5
aue = 6
param = {‘per’: per, ‘spd’: spd, ‘pit’: pit, ‘vol’: vol, ‘aue’: aue}
def generate_request_urltext:
url = ”
body = urllib.parse.urlencode{‘tex’: text, ‘tok’: token, ‘cuid’: ‘123456PYTHON’, ‘lan’: ‘zh’, ‘ctp’: 1}
request_url = url + ‘?’ + body
return request_url
def get_audio_contenturl:
response = requests.geturl
return response.content
def get_audio_filecontent, filename:
with openfilename, ‘wb’ as f:
f.writecontent
def play_audiofilename:
wf
“`
