This paper presents a technique for estimating HMM model parameters for noisy speech from given clean speech HMM and noise HMM. The model parameters are estimated by approximating the non-linear function governing the relationship between speech and noise, by a Lagrange polynomial, and thus enabling the distribution of corrupted speech parameters to have a closed form. The method is computation...

This paper addresses the problem of automatic word boundary detection in the presence of noise. We first propose an adaptive time-frequency (ATF) parameter for extracting both the time and frequency features of noisy speech signals. The ATF parameter extends the TF parameter proposed by Junqua et al. from single band to multiband spectrum analysis, where the frequency bands help to make the dis...

This paper proposes an environmental noise classification method using kernel principal component analysis (KPCA) for robust speech recognition. Once the type of noise is identified, speech recognition performance can be enhanced by selecting the identified noise specific acoustic model. The proposed model applies KPCA to a set of noise features such as normalized logarithmic spectrums (NLS), a...

Various approaches focused on noise-robustness have been investigated with the aim of using an automatic speech recognition (ASR) system in practical environments. We have previously proposed a distinctive phonetic feature (DPF) parameter set for a noise-robust ASR system, which reduced the effect of high-level additive noise[1]. This paper describes an attempt to replace normal distributions (...

The study of the effects of typographical factors on lexical access has been rather neglected in the literature on visual-word recognition. Indeed, current computational models of visual-word recognition employ an unrefined letter feature level in their coding schemes. In a letter recognition experiment, Pelli, Burns, Farell, and Moore-Page (2006), letters in Bookman boldface produced more effi...

Recognition performance decreases when recognition systems are used over the telephone network, especially wireless network and noisy environments. It appears that non efficient speech/non-speech detection is a very important source of this degradation. Therefore, speech detector robustness to noise is a challenging problem to be examined, in order to improve recognition performance for the ver...

The use of listening difficulty ratings of speech communication in rooms is explored because, in common situations, word recognition scores do not discriminate well among conditions that are near to acceptable. In particular, the benefits of early reflections of speech sounds on listening difficulty were investigated and compared to the known benefits to word intelligibility scores. Listening t...