双十二语音识别推荐

import speech_recognition as sr
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import linear_kernel

# 初始化语音识别器
recognizer = sr.Recognizer()

# 获取语音输入
with sr.Microphone() as source:
    print("请说话...")
    audio = recognizer.listen(source)

try:
    # 将语音转换为文本
    text = recognizer.recognize_google(audio, language='zh-CN')
    print(f"你说的是: {text}")

    # 示例商品列表及其描述
    products = {
        "手机": "最新款智能手机，性能强大。",
        "耳机": "高品质无线耳机，音质出色。",
        "笔记本": "轻薄便携笔记本，适合办公旅行。"
    }

    # 将商品描述转换为TF-IDF向量
    tfidf = TfidfVectorizer(stop_words='english')
    tfidf_matrix = tfidf.fit_transform(products.values())

    # 计算文本与商品描述的相似度
    query_vector = tfidf.transform([text])
    cosine_similarities = linear_kernel(query_vector, tfidf_matrix).flatten()

    # 获取最相似的商品
    related_products_indices = cosine_similarities.argsort()[:-3:-1]
    recommended_products = [list(products.keys())[i] for i in related_products_indices]

    print("推荐商品:")
    for product in recommended_products:
        print(f"- {product}: {products[product]}")

except sr.UnknownValueError:
    print("无法识别语音")
except sr.RequestError as e:
    print(f"无法请求结果; {e}")