Covers: implementation of Speech Recognition with Connectionist Temporal Classification
Estimated time needed to finish: 120 minutes
Questions this item addresses:
  • How do you build a speech recognition model from scratch with a connectionist temporal classification loss function?
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Read the article and try out the implementation.

Author(s) / creator(s) / reference(s)
AssemblyAI
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Create Your First Speech-to-text Model With Connectionist Temporal Classification

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Total time needed: ~4 hours
Objectives
Learn about methods of speech recognition, and create your own speech recognition model that recognizes speech on-the-fly
Potential Use Cases
People creating a speech recognition model, or people using an existing speech recognition model that want to understand and tune it better
Who is This For ?
BEGINNERData scientists new to speech recognition
Click on each of the following annotated items to see details.
Resources5/5
ARTICLE 1. Speech Recognition — Deep Speech, CTC, Listen, Attend, and Spell
  • What are the different methods of speech recognition?
25 minutes
ARTICLE 2. Sequence Modeling with CTC
  • What is the mathematical background to connectionist temporal classification?
15 minutes
VIDEO 3. Real-time Speech to Text with DeepSpeech - Getting Started on Windows and Transcribe Microphone Free
  • How do you run the Deep Speech speech recognition model, which was trained with connectionist temporal classification?
40 minutes
ARTICLE 4. Train Your Own Speech Recognition Model in 5 Simple Steps
  • How do you tune an existing connectionist temporal classification speech recognition model?
30 minutes
ARTICLE 5. Building an End-to-End Speech Recognition Model in PyTorch
  • How do you build a speech recognition model from scratch with a connectionist temporal classification loss function?
120 minutes

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