stem/Speech/NLP/Recognition.md

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1. Automatic Speech Recognition
- Spoken words to machine-readable form
2. Natural language understanding
- High level cognitive interpretation
- Structure
- Meaning
- Intention
# Automatic Speech Recognition
## Applications
- Business/desktop apps
- Dictation
- Voice commands
- Voice enabled services/apps
- Siri
- Home automation
- Game & Entertainment
- Education
- Speech therapy/Rehab
- Hearing assistance
- Live CC
## Challenges
- Speaker dependency
- Accent
- Emotion
- Vocab size
- Slang
- Isolated words vs Continuous speech
- Hard to segment continuous speech
- Language constraints & Knowledge sources
- Training source is critical
- Acoustic ambiguity
- Similar sounding speech
- Noise robustness
- Background noise
- Reverberation
# Speech Diarisation
- Who speaks when?
- Split stream into homogenous segments for identity
- Structure stream into speaker turns
- Provide speaker identity
- Combination of
- Speaker segmentation
- Speaker changes in stream
- Speaker clustering
- Grouping segments together on basis of characteristics
- Gaussian mixture model
- HMM
- Bottom-up
- More popular
- Succession of clusters
- Merge redundant clusters
- Remaining belong to speakers
- Top-down
- Single cluster
- Iteratively split until speaker clusters