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Probabilistic finite-state machines - part i.
| Content Provider | CiteSeerX |
|---|---|
| Author | Casacuberta, F. Vidal, E. Higuera, C. De La Carrasco, R. C. Thollard, F. |
| Abstract | Probabilistic finite-state machines are used today in a variety of areas in pattern recognition, or in fields to which pattern recognition is linked: computational linguistics, machine learning, time series analysis, circuit testing, computational biology, speech recognition and machine translation are some of them. In part I of this paper we survey these generative objects and study their definitions and properties. In part II, we will study the relation of probabilistic finite-state automata with other well known devices that generate strings as hidden Markov models and n-grams, and provide theorems, algorithms and properties that represent a current state of the art of these objects. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Speech Recognition Probabilistic Finite-state Machine Probabilistic Finite-state Automaton Computational Linguistics Machine Translation Computational Biology Machine Learning Probabilistic Finite-state Machine Part Pattern Recognition Circuit Testing Current State Time Series Analysis Part Ii Hidden Markov Model Generative Object |
| Content Type | Text |
| Resource Type | Article |
