This work assesses different approaches for speech and non-speech segmentation of audio data and proposes a new, high-level representation of audio signals based on phoneme recognition features suitable for speech/non-speech discrimination tasks. Unlike previous model-based approaches, where speech and non-speech classes were usually modeled by several models, we develop a representation where ...

We present a method for audio-visual classification of Swedish phonemes, to be used in computer-assisted pronunciation training. The probabilistic kernel-based method is applied to the audio signal and/or either a principal or an independent component (PCA or ICA) representation of the mouth region in video images. We investigate which representation (PCA or ICA) that may be most suitable and t...

This paper examines the applicability of some learning techniques to the classification of phonemes. The methods tested were artificial neural nets (ANN), support vector machines (SVM) and Gaussian mixture modeling. We compare these methods with a traditional hidden Markov phoneme model (HMM) working with the linear prediction-based cepstral coefficient features (LPCC). We also tried to combine...

the phoneme /l/ is one of the phonemes of persian, which has different origins. a few of which is unknown. this article studies the historical change of /l/ phoneme and phonemes and clusters which are the origins of /l/, from proto indo- european to indo- iranian, old iranian and middle and new persian. in adition, the historical change of other phonems such as group of consonants , which are o...

1. Introduction The performance of speech recognition algorithms degrades considerably due to speaker variability. Aside from gender, the largest cause for speaker variability is accent. If the accent of a speaker can be determined automatically, then accent-specific speech recognition models can be used, thereby increasing speech recognition accuracy. In this study, the problem of accent class...

A controversial issue in neurolinguistics is whether basic neural auditory representations found in many animals can account for human perception of speech. This question was addressed by examining how a population of neurons in the primary auditory cortex (A1) of the naive awake ferret encodes phonemes and whether this representation could account for the human ability to discriminate them. Wh...

For phoneme classification, this paper describes an acoustic model based on the variational Gaussian process dynamical system (VGPDS). The nonlinear and nonparametric acoustic model is adopted to overcome the limitations of classical hidden Markov models (HMMs) in modeling speech. The Gaussian process prior on the dynamics and emission functions respectively enable the complex dynamic structure...