This article presents a new feature extraction technique based on the temporal tracking of clusters in spectro-temporal features space. In the proposed method, auditory cortical outputs were clustered. The attributes of speech clusters were extracted as secondary features. However, the shape and position of speech clusters change during the time. The clusters temporally tracked and temporal tra...

This paper examines statistical models for phoneme classification. We compare the performance of our phoneme classification system using Gaussian mixture (GMM) phoneme models with systems using hidden Markov phoneme models (HMM). Measurements show that our model’s performance is comparable with HMM models in context independent phoneme classification.

the geometric distribution of states duration is one of the main performance limiting assumptions of hidden markov modeling of speech signals. stochastic segment models, generally, and segmental hmm, specifically, overcome this deficiency partly at the cost of more complexity in both training and recognition phases. in this paper, a new duration modeling approach is presented. the main idea of ...

Speech recognition consists of converting input sound into a sequence phonemes, then finding text for the using language models. Therefore, phoneme classification performance is critical factor successful implementation speech system. However, correctly distinguishing phonemes with similar characteristics still challenging problem even state-of-the-art methods, and errors are hard to be recover...

We explore neural higher-order input-dependent factors in linear-chain conditional random fields (LC-CRFs) for sequence labeling. Higher-order LC-CRFs with linear factors are wellestablished for sequence labeling tasks, but they lack the ability to model non-linear dependencies. These non-linear dependencies, however, can be efficiently modelled by neural higher-order input-dependent factors wh...

Phonemes in the English language can be represented using either parallel or hierarchical distinctive speech features. There have been a number of efforts to integrate multiple information sources but none of these efforts addressed the issue of combining multiple sets of articulatory/linguistic features with different organization topologies. In this study, we combine a frame-based parallel sp...