Create a lexicon and Hidden Markov Model (HMM) module for processing words and sentences extracted from a voice model. The goal is to build reusable components that allow further natural language processing and recognition tasks on the output of an existing voice-to-text system.
Tasks:
- Design and implement a lexicon to map recognized phonemes to words
- Build an HMM model for context-aware sequence modeling of extracted words/sentences
- Integrate the lexicon and HMM so they work together to process the voice model's output
- Write documentation and usage examples for working with words and sentences after voice extraction
Acceptance Criteria:
- Able to process a sequence of tokens/words from a voice model and output normalized sentences
- Lexicon and HMM components are modular and well-documented
- Example scripts for inference and demonstration are provided
Scope Constraints:
- This issue does not include voice model development; expects already extracted words/sentences as input
Create a lexicon and Hidden Markov Model (HMM) module for processing words and sentences extracted from a voice model. The goal is to build reusable components that allow further natural language processing and recognition tasks on the output of an existing voice-to-text system.
Tasks:
Acceptance Criteria:
Scope Constraints: