SpeechCommAI is a console program for predicting up to 35 spoken words.
This project can be used to recognize speech commands, recorded in real-time. Prediction is made by a convolutional neural network based on Keras, learned on the TensorFlow database. Using special options, users can download a dataset, preprocess it and teach the program themselves.
- backward
- bed
- bird
- cat
- dog
- down
- eight
- five
- follow
- forward
- four
- go
- happy
- house
- learn
- left
- marvin
- nine
- no
- off
- on
- one
- right
- seven
- sheila
- six
- stop
- three
- tree
- two
- up
- visual
- wow
- yes
- zero
- python (3.7+)
- pip
- required libraries listet in the
requirements.txtfile
You can install requirements by the follwing command:
pip install -r requirements.txt
To use this program run main.py in the command line:
python main.py <option>
As an <option> one of the following can be selected:
D – Download the raw dataset
P – Pre-process the dataset
T – Train the model
L – Live record
In addition, the T and L options can take one more optional argument specifying the type of set of words to be trained. The word sets are available in the config.toml file. If the name of the set is not specified, the program will accept the entire set of 35 words by default.
Machine learning:
- TensorFlow - version 2.9.1
- Keras - version 2.9.0
Audio processing:
- librosa - version 0.9.1
- PyAudio - version 0.2.12
Plots:
- matplotlib - version 3.5.1
- scikit-learn - version 1.1.2
Visualization of the learned network (confusion matrix):
The model's learning history:
Created by @miolows - feel free to contact me!