A key problem in the use of context-dependent hidden Markov models is the need to balance the desired model complexity with the amount of available training data. This paper describes a method which uses a simple agglomerative algorithm to cluster and tie acoustically similar states. The main proper
Testing for two states in a hidden Markov model
✍ Scribed by Jörn Dannemann; Hajo Holzmann
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- French
- Weight
- 556 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0319-5724
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