The development of Automatic Speech Recognition techniques continues to accelerate. Already an established technology, Automatic Speech Recognition is growing by leaps and bounds each year, especially as artificial intelligence contributes to evolution. A crucial building block of artificial intelligence is deep learning.
What is Deep Learning?
Deep learning refers to the process of a computer model learning how to do classification tasks by example, directly from audio, text, or images. These models are trained using very large sets of data and neural network topologies with many hidden layers, to which the word “deep” refers. Deep Neural Networks can achieve state-of-the-art performance in many different fields, even exceeding human-level performance on some of them.
What are Neural Networks?
More specifically, neural networks are a series of algorithms, whose job it is to identify relationships within a set of data, a process that simulates the way a human brain identifies underlying connections. When it comes to speech technology, neural networks enable us to push the limits of speech recognition.
Which Neural Network for Automatic Speech Recognition?
Deep Neural Networks are transforming the way humans interact, playing an important role in the technological revolution of artificial intelligence. At LumenVox, our Research and Development team is currently utilizing Time Depth Separable Convolutional Neural Networks (TDS CNN).
Convolutional Neural Networks are advantageous for a few reasons: They are computationally efficient, making them highly useful for mobile applications, and they have fewer knobs to toy with, fewer parameters to adjust. That means LumenVox customers get an ASR engine with greater speech recognition accuracy without requiring more compute performance, encouraging greater efficiency and performance.
LumenVox’ deep learning technology is applied to many of our technologies, including Automatic Speech Recognizer, Natural Language Processing, and Voice Biometrics. To learn more about our comprehensive stack, or to take an even deeper dive into deep learning, contact us today!