https://github.com/parthvadhadiya/tensorflow-speech-recognition-challenge
this repository contains end to end python script to train speech data provided by google, evaluate testing data, and submite to competition
https://github.com/parthvadhadiya/tensorflow-speech-recognition-challenge
competition kaggle-competition keras librosa spectrum speech-data speech-recognition tensorflow
Last synced: 3 months ago
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this repository contains end to end python script to train speech data provided by google, evaluate testing data, and submite to competition
- Host: GitHub
- URL: https://github.com/parthvadhadiya/tensorflow-speech-recognition-challenge
- Owner: parthvadhadiya
- Created: 2017-12-20T15:56:04.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-12-20T16:42:13.000Z (over 8 years ago)
- Last Synced: 2025-06-29T06:03:37.135Z (about 1 year ago)
- Topics: competition, kaggle-competition, keras, librosa, spectrum, speech-data, speech-recognition, tensorflow
- Language: Python
- Size: 10.7 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# TensorFlow-Speech-Recognition-Challenge
this repository contains end-to-end pipe line to train different speech data provided by google, evaluate testing data, and submite to kaggle competition. (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge)
## Getting Started
clone repo. :- git clone https://github.com/parthvadhadiya/TensorFlow-Speech-Recognition-Challenge
download dataset :- https://www.kaggle.com/c/tensorflow-speech-recognition-challenge/data
### Installing Prerequisites
=> Python3 -3.5.2
=> NumPy -1.13.1
for store and manupulate multidimensional array,
installing numpy:- sudo pip3 install numpy (obviously for windows you can enter without sudo command).
=> librosa -0.5.1
for audio analysis
installing librosa:- sudo pip3 install librosa(you can also use scipy's wav module)
=> keras -2.0.6
high-level neural networks API
installing keras:- https://keras.io/#installation
=> tqdm -4.19.4
an awsome progress meter in terminal
intalling tqdm :- sudo pip3 install tqdm