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Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.
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Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.
Deep Learning Framework Proficiency, Intermediate Python
Learn the basics of how computers understand spoken words and get familiar with the most common VUI applications. Set up your AWS account and build Alexa skill with an existing template.
Learn the basics of Amazon AWS and create your own fully functional Alexa skill using Amazon’s API. Deploy your skill for everyone to use it
Learn the pipeline used for speech recognition and learn to process and extract features from sound signals. Learn to build probabilistic and machine learning language models in order to extract words and grammar from sound signals.
Build a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline. The model will convert raw audio into feature representations, which will then turn them into transcribed text. Begin by investigating a dataset that will be used to train and evaluate their models. Your algorithm will first convert any raw audio to feature representations that are commonly used for ASR. Then build neural networks that map these features to transcribed text.
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
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Validate your understanding of concepts learned by checking the output and quality of your code in real-time.
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Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Dana is an electrical engineer with a Masters in Computer Science from Georgia Tech. Her work experience includes software development for embedded systems in the Automotive Group at Motorola, where she was awarded a patent for an onboard operating system.
Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.
On average, successful students take 1 month to complete this program.
No. This Course accepts all applicants regardless of experience and specific background.
A well-prepared learner has experience with Convolutional neural networks, Recurrent neural networks, Intermediate Python, PyTorch, Basic calculus, Linear algebra, Basic probability, and Jupyter notebooks.
This course is comprised of content and curriculum to support one project. We estimate that students can complete the program in one month.
The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.
Learners will need Anaconda with Python 3.5 and supporting packages