jfsantos

!obj:pylearn2.train.Train {
    dataset: &train !obj:research.code.pylearn2.datasets.timit.TIMIT {
        which_set: 'train',
        frame_length: &flen 160,
        frames_per_example: &fpe 1,
        samples_to_predict: &ylen 1,
        n_next_phones: 1,
        n_prev_phones: 1,
        #start: 0,
        #stop: 100,

jfsantos

using BinDeps

@BinDeps.setup

@unix_only begin
    ecos = library_dependency("ecos",aliases=["libecos"])
end

provides(Sources, URI("https://github.com/ifa-ethz/ecos/archive/master.zip"),
    [ecos], os = :Unix, unpacked_dir="ecos-master")

jfsantos

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import wave
import numpy as np
import scipy as sp

WINSIZE=8192
sound='sound.wav'

def read_signal(filename, winsize):

jfsantos

jfsantos

### Keybase proof

I hereby claim:

  * I am jfsantos on github.
  * I am jfsantos (https://keybase.io/jfsantos) on keybase.
  * I have a public key whose fingerprint is C422 70CC D7E3 C653 09B0  E52E 06AF B67E AD5E 95E5

To claim this, I am signing this object:

jfsantos

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import wave
import numpy as np
import scipy as sp

WINSIZE=8192
sound='sound.wav'

def read_signal(filename, winsize):

jfsantos

Traceback (most recent call last):

  File "<string>", line 1, in <module>

  File "/private/var/folders/z3/s0__77pd3n1bpym4f75hrzbc0000gn/T/pip_build_jfsantos/music21/setup.py", line 65, in <module>

    include_package_data=True,

  File "/Users/jfsantos/anaconda/envs/py3/lib/python3.3/distutils/core.py", line 148, in setup

jfsantos

from gammatone.fftweight import fft_gtgram
from scipy.io.matlab import loadmat

s = loadmat("test.mat")["s"][:,0]
fs = 16000

# gt_py has 260 frames
gt_py = fft_gtgram(s, fs, 0.010, 0.0025, 23, 125)

# gt_mat has 269 frames

jfsantos

ENV["MOCHA_USE_CUDA"] = "true"

using HDF5, JLD, Mocha

X = Array[]
push!(X, rand(Float32, 128,11*129,1,1))
y = Array[]
push!(y, rand(Float32, 128, 129, 1, 1))

#data_layer = AsyncHDF5DataLayer("train", "train.txt", 128, 1000, [:features, :targets], false, [])

jfsantos

import numpy as np
import scipy.signal as sig
from adaptfilt import lms

if __name__ == '__main__':
    import matplotlib.pyplot as plt
    from scipy.io import wavfile

    sigma = 0.1
    order = 100