122 resultados para cross-link
Resumo:
A non-weak link joining technique has been developed for YBCO pseudo-crystals fabricated by seeded peritectic solidification based on the formation of a liquid phase which segregates from the platelet boundaries at temperatures above = 920 °C. Electrical and magnetic measurements on these boundaries suggest that their irreversibility field can be as high as 7 T at 77 K in fully oxygenated pseudo-crystals joined along their crystallographic ab-planes which is comparable to the irreversibility behaviour of the adjacent YBCO grains. © 1999 IEEE.
Resumo:
Problem of DC link size in a stiff voltage-source inverter for electric drive is described in the paper. Advantages of advanced film capacitor technology over conventional one for DC link application are reviewed. Conventional DC link capacitor selection methods are questioned in view of advanced capacitor technology utilization in stiff voltage-source inverter. For capacitor selection maximum ripple rms current point is shown. DC link ripple current spectrum analysis under modern PWM techniques is presented. Some capacitor selection recommendations are given. The analysis has been aided greatly by computer modeling in PSpice. ©2005 IEEE.
Resumo:
This paper investigates several approaches to bootstrapping a new spoken language understanding (SLU) component in a target language given a large dataset of semantically-annotated utterances in some other source language. The aim is to reduce the cost associated with porting a spoken dialogue system from one language to another by minimising the amount of data required in the target language. Since word-level semantic annotations are costly, Semantic Tuple Classifiers (STCs) are used in conjunction with statistical machine translation models both of which are trained from unaligned data to further reduce development time. The paper presents experiments in which a French SLU component in the tourist information domain is bootstrapped from English data. Results show that training STCs on automatically translated data produced the best performance for predicting the utterance's dialogue act type, however individual slot/value pairs are best predicted by training STCs on the source language and using them to decode translated utterances. © 2010 ISCA.
Resumo:
The standard, ad-hoc stopping criteria used in decision tree-based context clustering are known to be sub-optimal and require parameters to be tuned. This paper proposes a new approach for decision tree-based context clustering based on cross validation and hierarchical priors. Combination of cross validation and hierarchical priors within decision tree-based context clustering offers better model selection and more robust parameter estimation than conventional approaches, with no tuning parameters. Experimental results on HMM-based speech synthesis show that the proposed approach achieved significant improvements in naturalness of synthesized speech over the conventional approaches. © 2011 IEEE.
Resumo:
Hidden Markov model (HMM)-based speech synthesis systems possess several advantages over concatenative synthesis systems. One such advantage is the relative ease with which HMM-based systems are adapted to speakers not present in the training dataset. Speaker adaptation methods used in the field of HMM-based automatic speech recognition (ASR) are adopted for this task. In the case of unsupervised speaker adaptation, previous work has used a supplementary set of acoustic models to estimate the transcription of the adaptation data. This paper first presents an approach to the unsupervised speaker adaptation task for HMM-based speech synthesis models which avoids the need for such supplementary acoustic models. This is achieved by defining a mapping between HMM-based synthesis models and ASR-style models, via a two-pass decision tree construction process. Second, it is shown that this mapping also enables unsupervised adaptation of HMM-based speech synthesis models without the need to perform linguistic analysis of the estimated transcription of the adaptation data. Third, this paper demonstrates how this technique lends itself to the task of unsupervised cross-lingual adaptation of HMM-based speech synthesis models, and explains the advantages of such an approach. Finally, listener evaluations reveal that the proposed unsupervised adaptation methods deliver performance approaching that of supervised adaptation.