Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma
You can get the list of supported formats with:
ffmpeg -formats
Convert WAV to MP3, mix down to mono (use 1 audio channel), set bit rate to 64 kbps and sample rate to 22050 Hz:
| -- Remove the history from | |
| rm -rf .git | |
| -- recreate the repos from the current content only | |
| git init | |
| git add . | |
| git commit -m "Initial commit" | |
| -- push to the github remote repos ensuring you overwrite history | |
| git remote add origin git@github.com:<YOUR ACCOUNT>/<YOUR REPOS>.git |
| ''' | |
| Train | |
| python 3.6.4 | |
| tensorflow 0.12.1 | |
| 2018-06-30 | |
| ''' | |
| import ipdb as pdb | |
| import os | |
| import utils |
| ''' | |
| Train | |
| python 3.6.4 | |
| tensorflow 0.12.1 | |
| 2018-06-30 | |
| ''' | |
| import ipdb as pdb | |
| import os | |
| import utils |
| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| import sys, time, threading, abc | |
| from optparse import OptionParser | |
| def parse_options(): | |
| parser = OptionParser() | |
| parser.add_option("-t", action="store", type="int", dest="threadNum", default=1, | |
| help="thread count [1]") |
| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |
| """ Deep Auto-Encoder implementation | |
| An auto-encoder works as follows: | |
| Data of dimension k is reduced to a lower dimension j using a matrix multiplication: | |
| softmax(W*x + b) = x' | |
| where W is matrix from R^k --> R^j | |
| A reconstruction matrix W' maps back from R^j --> R^k |
