Abstract. This paper has as main goal to develop a hybrid expert system to minimize some of the complexity problems related to arti cial intelligence eld. For instance, we can ment...
Lourdes Mattos Brasil, Fernando Mendes de Azevedo,...
This paper presents a novel training method of an eigenvoice Gaussian mixture model (EV-GMM) effectively using non-parallel data sets for many-to-many eigenvoice conversion, which...
We present a machine translation framework that can incorporate arbitrary features of both input and output sentences. The core of the approach is a novel decoder based on lattice...
This paper takes phonetic information into account for data alignment in text-independent voice conversion. Hidden Markov Models are used for representing the phonetic structure o...
Meng Zhang, Jiaohua Tao, Jani Nurminen, Jilei Tian...
We have developed a VLSI chip for 5,000 word speakerindependent continuous speech recognition. This chip employs a context-dependent HMM (hidden Markov model) based speech recogni...