[自然语言处理|NLP]NLP在多模态融合的应用：从原理到实践

# 示例代码：文本与图像融合的场景描述生成
import openai
from PIL import Image

openai.api_key = "YOUR_API_KEY"

def generate_scene_description(image_path):
    with open(image_path, "rb") as image_file:
        image_data = image_file.read()

    response = openai.Image.create(
        file=image_data,
        model="text-davinci-003",
        prompt="描述这张图片中的场景。",
        max_tokens=100
    )

    return response.choices[0].text.strip()

# 示例
image_path = "path/to/your/image.jpg"
scene_description = generate_scene_description(image_path)

print("场景描述:", scene_description)

# 示例代码：文本与语音融合的语音指令理解
import openai
import speech_recognition as sr

openai.api_key = "YOUR_API_KEY"

def process_audio_command(audio_path):
    recognizer = sr.Recognizer()
    with sr.AudioFile(audio_path) as source:
        audio_data = recognizer.record(source)

    text_command = recognizer.recognize_google(audio_data, language="en-US")

    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=f"用户语音指令：{text_command}\n",
        max_tokens=100
    )

    return response.choices[0].text.strip()

# 示例
audio_path = "path/to/your/audio.wav"
processed_command = process_audio_command(audio_path)

print("处理后的指令:", processed_command)