Articulatory feature recognition using dynamic Bayesian networks
نویسندگان
چکیده
منابع مشابه
Articulatory feature recognition using dynamic Bayesian networks
We describe a dynamic Bayesian network for articulatory feature recognition. The model is intended to be a component of a speech recognizer that avoids the problems of conventional “beads-on-a-string” phoneme-based models. We demonstrate that the model gives superior recognition of articulatory features from the speech signal compared with a stateof-the art neural network system. We also introd...
متن کاملHidden feature models for speech recognition using dynamic Bayesian networks
In this paper, we investigate the use of dynamic Bayesian networks (DBNs) to explicitly represent models of hidden features, such as articulatory or other phonological features, for automatic speech recognition. In previous work using the idea of hidden features, the representation has typically been implicit, relying on a single hidden state to represent a combination of features. We present a...
متن کاملFeature Dynamic Bayesian Networks
Feature Markov Decision Processes (ΦMDPs) [Hut09] are well-suited for learning agents in general environments. Nevertheless, unstructured (Φ)MDPs are limited to relatively simple environments. Structured MDPs like Dynamic Bayesian Networks (DBNs) are used for large-scale realworld problems. In this article I extend ΦMDP to ΦDBN. The primary contribution is to derive a cost criterion that allows...
متن کاملAutomatic speech recognition using dynamic bayesian networks with both acoustic and articulatory variables
Current technology for automatic speech recognition (ASR) uses hidden Markov models (HMMs) that recognize spoken speech using the acoustic signal. However, no use is made of the causes of the acoustic signal: the articulators. We present here a dynamic Bayesian network (DBN) model that utilizes an additional variable for representing the state of the articulators. A particular strength of the s...
متن کاملAutomatic Speech Recognition using Dynamic Bayesian Networks
New ideas to improve automatic speech recognition have been proposed that make use of context user information such as gender, age and dialect. To incorporate this information into a speech recognition system a new framework is being developed at the mmi department of the ewi faculty at the Delft University of Technology. This toolkit is called Gaia and makes use of Dynamic Bayesian networks. I...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Speech & Language
سال: 2007
ISSN: 0885-2308
DOI: 10.1016/j.csl.2007.03.002