文件名称:
feature_extraction.py
开发工具:
文件大小: 3kb
下载次数: 0
上传时间: 2020-05-27
详细说明：# -*- coding: utf-8 -*-
import numpy as np
import librosa
import random
def extract_power(y, sr, size=3):
"""
extract log mel spectrogram feature
:param y: the input signal (audio time series)
:param sr: sample rate of 'y'
:param size: the length (seconds) of random crop from original audio, default as 3 seconds
:return: log-mel spectrogram feature
"""
# normalization
y = y.astype(np.float32)
normalization_factor = 1 / np.max(np.abs(y))
y = y * normalization_factor
# random crop
start = random.randint(0, len(y) - size * sr)
y = y[start: start + size * sr]
# extract log mel spectrogram #####
powerspec = np.abs(librosa.stft(y,n_fft=128, hop_length=1024)) ** 2
#logmelspec = librosa.power_to_db(melspectrogram)
return powerspec
def extract_logmel(y, sr, size=3):
"""
extract log mel spectrogram feature
:param y: the input signal (audio time series)
:param sr: sample rate of 'y'
:param size: the length (seconds) of random crop from original audio, default as 3 seconds
:return: log-mel spectrogram feature
"""
# normalization
y = y.astype(np.float32)
normalization_factor = 1 / np.max(np.abs(y))
y = y * normalization_factor
# random crop
start = random.randint(0, len(y) - size * sr)
y = y[start: start + size * sr]
# extract log mel spectrogram #####
melspectrogram = librosa.feature.melspectrogram(y=y, sr=sr, n_fft=2048, hop_length=1024, n_mels=90)
logmelspec = librosa.power_to_db(melspectrogram)
return logmelspec
def extract_mfcc(y, sr, size=3):
"""
extract MFCC feature
:param y: np.ndarray [shape=(n,)], real-valued the input signal (audio time series)
:param sr: sample rate of 'y'
:param size: the length (seconds) of random crop from original audio, default as 3 seconds
:return: MFCC feature
"""
# normalization
y = y.astype(np.float32)
normalization_factor = 1 / np.max(np.abs(y))
(系统自动生成,下载前可以参看下载内容)
下载文件列表
相关说明
- 本站资源为会员上传分享交流与学习,如有侵犯您的权益,请联系我们删除.
- 本站是交换下载平台，提供交流渠道，下载内容来自于网络，除下载问题外，其它问题请自行百度。
- 本站已设置防盗链，请勿用迅雷、QQ旋风等多线程下载软件下载资源，下载后用WinRAR最新版进行解压.
- 如果您发现内容无法下载，请稍后再次尝试；或者到消费记录里找到下载记录反馈给我们.
- 下载后发现下载的内容跟说明不相乎，请到消费记录里找到下载记录反馈给我们，经确认后退回积分.
- 如下载前有疑问，可以通过点击"提供者"的名字，查看对方的联系方式，联系对方咨询.
