Saturday, September 25Digital Marketing Journals

Applications of Deep Learning in Speech Recognition for Kids | by SoapBox


SoapBox
This image depicts deep learning. It shows a human brain.

Welcome to Lesson 3 in our “Lessons from Our Voice Engine” series, featuring high level insights from our Engineering and Speech Tech teams on how our voice engine works. This lesson is from Siva Reddy Gangireddy, a Senior Speech Recognition Scientist on our Speech Tech team.

Machine learning is a group of algorithms that focus on learning from data to make predictions and decisions without any explicit programming. It usually involves training a model on huge amounts of data to learn patterns so that predictions and decisions can then be made on new data. For example, the smart speakers we use in daily life are based on machine learning algorithms.

Deep learning is a form of machine learning that’s based on neural networks, a set of algorithms designed to mimic the function of the human brain. Any network with more than three layers is considered a deep neural network and the input is processed through those several layers to predict the desired output. Deep neural networks require huge amounts of data and are extensively used in speech recognition and image recognition. At SoapBox Labs, our models are trained on thousands of hours of audio data and evaluated on in-house datasets regularly.

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Catch up on our previous “Lessons from Our Voice Engine”:

#1: Natural Language Processing (NLP)

#2: Custom Language Models (CLMs)

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