What are the steps to update the models in the training set?
- Recompute the forward and backward likelihoods
- Recompute the transition and occupation likelihoods
- Increment the transition and output accumulators
These steps are essential for refining the model parameters during training.
In the context of model updating, what does Ri represent?
Re-estimated parameters of the model
This notation indicates the updated values for the model parameters after re-estimation.
What types of utterances are used in the re-estimation process?
- Labelled Utterances
- Unlabelled Utterances
Labelled utterances provide specific transcriptions, while unlabelled utterances are used for general training.
What is the purpose of HInit, HRest, and HCompV in HMM training?
- HInit: Initial model parameters
- HRest: Re-estimated model parameters
- HCompV: Component model parameters
These components are crucial for the Hidden Markov Model (HMM) training process.
True or false: HMM training can be performed with variously labelled data.
TRUE
This flexibility allows for improved model performance across different datasets.
What does agglomerative clustering refer to in the context of HMM training?
A method for grouping data points based on similarity
This technique is often used to enhance the training process by organizing data effectively.
