{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\n#import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(os.listdir(\"../input\"))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"# Custom Imports\n\nfrom subprocess import check_output\nfrom scipy.io import wavfile","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"0ad95f0ee7ac932362fb7d85634944b451990592"},"cell_type":"code","source":"# processing silence files\ntrain_audio_path = '../input/train/audio'\n\nprint(check_output([\"ls\", \"../input/train/audio/_background_noise_\"]).decode(\"utf8\"))\n\ndef wavread(file):\n    sample_rate, samples = wavfile.read(str(train_audio_path) + '/' + file)\n    return np.array(samples)\n\nfiles = os.listdir(train_audio_path + '/_background_noise_')\n\ntot_files = 0\n\nfor f in files:\n    if not f.endswith('wav'):\n        continue\n\n    f_samples = wavread('/_background_noise_/'+f)\n    f_len = len(f_samples)\n    f_name = os.path.splitext(f)[0]\n\n    i = 0\n    \n    while i + 16000 <= f_len and i < int(82):\n        wavfile.write(f_name + '_' + str(i) + '.wav', 16000, f_samples[i*16000:i*16000+16000])\n        i = i + 1\n        tot_files = tot_files + 1\n\nprint(\"Silence files saved:\",tot_files)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"5327698e3f587de9088b1261e7cdedebf5b92100"},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}