Speech Recognition Course
This course offers a practical guide to building accurate, low-latency Automatic Speech Recognition (ASR) systems for short utterances, covering key techniques from feature extraction to deployment.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Speech Recognition Course provides a quick, hands-on route to developing precise, low-delay ASR for brief utterances. You'll cover feature extraction, decoding using beam search, integrating language models, pronunciation assessment, and confidence metrics. Delve into contemporary architectures, pre-trained models, assessment measures, and deployment considerations to build sturdy, privacy-focused speech applications.
Elevify advantages
Develop skills
- Construct solid ASR features: MFCCs, log-mel, SpecAugment in no time.
- Develop and adjust modern ASR models: CTC, encoder-decoder, Conformer, Whisper.
- Apply clever decoding: beam search, LM rescoring, confidence and OOV management.
- Assess speech systems: WER, latency, robustness, and pronunciation evaluation.
- Ready speech datasets: short-utterance planning, annotation, and non-native data.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
Your classes are perfect. I got the one-year package and finally have the chance to follow a range of topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...

Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the extra videos really help with learning.

Giulio CarloPrompt Engineering Student
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