In this post, we'll be looking at how to use TensorFlow.js and Node.js to build a speech recognition system.
We'll start by looking at how to setup the environment, then we'll get into the code.
The first thing we need to do is install TensorFlow.js. We can do that with the following command:
npm install @tensorflow/tfjs
Once that's done, we need to install the Node.js bindings for TensorFlow.js. We can do that with the following command:
npm install @tensorflow/tfjs-node
With that out of the way, we can now move on to the code.
We'll start by loading the TensorFlow.js library and the Node.js bindings. We can do that with the following code:
const tf = require('@tensorflow/tfjs');
require('@tensorflow/tfjs-node');
Next, we'll need to load the speech recognition library. We can do that with the following code:
const speech = require('@tensorflow-models/speech-commands');
With that out of the way, we can now move on to the fun part: the code.
We'll start by creating a new speech recognition model. We can do that with the following code:
const model = speech.createModel();
Next, we'll need to train the model. We can do that with the following code:
model.train({
fileNames: [
'file1.wav',
'file2.wav',
'file3.wav',
],
labels: [
'label1',
'label2',
'label3',
]
});
Once the model is trained, we can now use it to recognize speech. We can do that with the following code:
model.recognize(audio, (err, result) => {
if (err) {
console.error(err);
} else {
console.log(result);
}
});
And that's it! You now have a working speech recognition system.
In this post, we've seen how to use TensorFlow.js and Node.js to build a speech recognition system. We've started by looking at how to setup the environment, then we've gotten into the code.
If you're interested in learning more, I recommend checking out the following resources: