Base URL: https://www.google.com/speech-api/v1/recognize
It accepts POST requests with voice file encoded in FLAC format, and query parameters for control.
client
The client's name you're connecting from. For spoofing purposes, let's use chromium
lang
Speech language, for example, ar-QA for Qatari Arabic, or en-US for U.S. English
Backstory: I decided to crowdsource static site generator recommendations, so the following are actual real world suggested-to-me results. I then took those and sorted them by language/server and, just for a decent relative metric, their Github Watcher count. If you want a heap of other projects (including other languages like Haskell and Python) Nanoc has the mother of all site generator lists. If you recommend another one, by all means add a comment.
| from sklearn import linear_model | |
| from scipy import stats | |
| import numpy as np | |
| class LinearRegression(linear_model.LinearRegression): | |
| """ | |
| LinearRegression class after sklearn's, but calculate t-statistics | |
| and p-values for model coefficients (betas). | |
| Additional attributes available after .fit() |
People
 :bowtie: |
😄 :smile: |
😆 :laughing: |
|---|---|---|
😊 :blush: |
😃 :smiley: |
:relaxed: |
😏 :smirk: |
😍 :heart_eyes: |
😘 :kissing_heart: |
😚 :kissing_closed_eyes: |
😳 :flushed: |
😌 :relieved: |
😆 :satisfied: |
😁 :grin: |
😉 :wink: |
😜 :stuck_out_tongue_winking_eye: |
😝 :stuck_out_tongue_closed_eyes: |
😀 :grinning: |
😗 :kissing: |
😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |
| #!/usr/bin/env bash | |
| # | |
| # gh-dl-release! It works! | |
| # | |
| # This script downloads an asset from latest or specific Github release of a | |
| # private repo. Feel free to extract more of the variables into command line | |
| # parameters. | |
| # | |
| # PREREQUISITES | |
| # |
| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |
| def mirror_padding(images, filter_size): | |
| """ | |
| Mirror padding is used to apply a 2D convolution avoiding the border | |
| effects that one normally gets with zero padding. | |
| We assume that the filter has an odd size. | |
| To obtain a filtered tensor with the same output size, substitute | |
| a ``conv2d(images, filters, mode="half")`` with | |
| ``conv2d(mirror_padding(images, filters.shape), filters, mode="valid")``. |
