We investigated a robust speech feature extraction method using kernel PCA (Principal Component Analysis) for distorted speech recognition. Kernel PCA has been suggested for various image processing tasks requiring an image model, such as denoising, where a noise-free image is constructed from a noisy input image [1]. Much research for robust speech feature extraction has been done, but it rema...

One of the most useful applications of Confidence Measures (CMs) in Automatic Speech Recognition systems is early detection of incorrect recognition hypotheses. A purely acoustic basis for such a CM is particularly important when tracking errors resulting from Out of Vocabulary speech, background noise or keyword substitution. A commonly taken approach is to compute scores on subword units of t...

The performance of many noise-robust automatic speech recognition (ASR) methods, such as vector Taylor series (VTS) feature compensation, heavily depends on an estimation of the noise that contaminates speech. Therefore, providing accurate noise estimates for this kind of methods is crucial as well as a challenge. In this paper we investigate the use of deep neural networks (DNNs) to perform no...

This paper treats a linear transformation of word templates in a word recognition system. The object of the transformation, called LMR-transform, is to adapt the recogniser to a new acoustical environment. The transform is derived by linear regression on pairs of word utterances from two different acoustical environments. The use of the transform has been evaluated for recognition accuracy, spe...

environment List of unusual symbols used Number of pages: 26 Number of tables: 4 Number of figures: 1 List of Figures Fig. 1. Block diagram of the context-adaptive speech front-end with GMM-based clustering of the feature space in the first stage and mapping function for speech enhancement channel selection in the second stage. 22 List of Tables Table 1. Speech recognition performance (...

This paper presents an analysis of the word recognition error rate on an English subset of the MALACH corpus. The MALACH project is an NSF-funded research program related to the development of multilingual access to large audio archives. The archive of interest is a large collection of testimonies from 52,000 survivors, liberators, rescuers and witnesses of the Nazi Holocaust, assembled by the ...

Two-tone mnnasking, psychophysical tuning curves and pure-tone masking patterns were measured at 500 and 1000 Hz in 17 listeners having high-frequency sensorineural hearing loss due to noise exposure. Results were compared to similar data obtained from 20 normal-hearing young adults. In addition, measures of word-recognition ability, were ob 'tained in quiet and in noise for both Rroups. The pr...

We present our research on continuous speech recognition of the surface electromyographic signals that are generated by the human articulatory muscles. Previous research on electromyographic speech recognition was limited to isolated word recognition because it was very difficult to train phoneme-based acoustic models for the electromyographic speech recognizer. In this paper, we demonstrate ho...