[{"createTime":1735734952000,"id":1,"img":"hwy_ms_500_252.jpeg","link":"https://activity.huaweicloud.com/cps.html?fromacct=261f35b6-af54-4511-a2ca-910fa15905d1&utm_source=V1g3MDY4NTY=&utm_medium=cps&utm_campaign=201905","name":"华为云秒杀","status":9,"txt":"华为云38元秒杀","type":1,"updateTime":1735747411000,"userId":3},{"createTime":1736173885000,"id":2,"img":"txy_480_300.png","link":"https://cloud.tencent.com/act/cps/redirect?redirect=1077&cps_key=edb15096bfff75effaaa8c8bb66138bd&from=console","name":"腾讯云秒杀","status":9,"txt":"腾讯云限量秒杀","type":1,"updateTime":1736173885000,"userId":3},{"createTime":1736177492000,"id":3,"img":"aly_251_140.png","link":"https://www.aliyun.com/minisite/goods?userCode=pwp8kmv3","memo":"","name":"阿里云","status":9,"txt":"阿里云2折起","type":1,"updateTime":1736177492000,"userId":3},{"createTime":1735660800000,"id":4,"img":"vultr_560_300.png","link":"https://www.vultr.com/?ref=9603742-8H","name":"Vultr","status":9,"txt":"Vultr送$100","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":5,"img":"jdy_663_320.jpg","link":"https://3.cn/2ay1-e5t","name":"京东云","status":9,"txt":"京东云特惠专区","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":6,"img":"new_ads.png","link":"https://www.iodraw.com/ads","name":"发布广告","status":9,"txt":"发布广告","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":7,"img":"yun_910_50.png","link":"https://activity.huaweicloud.com/discount_area_v5/index.html?fromacct=261f35b6-af54-4511-a2ca-910fa15905d1&utm_source=aXhpYW95YW5nOA===&utm_medium=cps&utm_campaign=201905","name":"底部","status":9,"txt":"高性能云服务器2折起","type":2,"updateTime":1735660800000,"userId":3}]
劣质的麦克风在录音时会把电流和嗡嗡的背景声录进去,通过对噪声取样去除频率可以达到降噪的目的。
主要步骤:
1. 噪声取样
2. 统计频率
3. 移除频率
代码如下:
'''采样降噪''' def test2(n, y, sr): indexs = librosa.effects.split(y, top_db=25-n)
noicefrequencies = [] for i in indexs: frequencies, D =
librosa.ifgram(y[i[0]:i[1]], sr=sr, n_fft=22000) frequencies =
frequencies.astype(int) noicefrequencies += frequencies.flatten().tolist() c =
Counter(noicefrequencies) noicefrequencies = set(map(lambda x: x[0] // 2 * 2,
c.most_common(400))) frequencies, D = librosa.ifgram(y, sr=sr) tempD =
D.copy().astype(int) tempD = tempD // 2 * 2 count = 0 for i in
range(D.shape[0]): for j in range(D.shape[1]): if tempD[i][j] in
noicefrequencies: count += 1 D[i][j] = 0 print(count) return librosa.istft(D)