Influence of G729 Speech Coding on AutomaticSpeaker Recognition in VoIP Applications

A method is described for predicting acoustic feature variability by analyzing the consensus and relative entropy of phoneme posterior probability distributions

Another approach is used for Multi-component Recurrent Neural Networks (MRNNs) [2] implementation, where bilingual automatic speech recognition systems with a large LVCSR dictio-

Given the definition of the desired magnitude response a window function can be computed using methods similar to those used for the design of optimal linear phase FIR

On the other hand, the effect of the vocal tract shape on the intrinsic variability of the speech signal between different speakers has been widely studied and many solutions to

The methodology consists in introducing semantic information by using a class-based statistical language model for which classes directly correspond to IF entries.. With

d(Ψ src , Ψ tgt ) = hΨ src , Ψ tgt i (8) In the context of voice casting, the advantage of the multi-label scoring is double : first, the multi-label scoring can be used to

Indeed, we obtain a significant decrease of the word error rate with experiments done on French broadcast news from the ESTER corpus; we also notice an improvement of the sentence

In general, at every distance, the phonemes that had high recognition scores were the ones showing large differences with noise and therefore high amplitude levels of some of