OCR is an error prone process when input images are degraded Most current OCR techniques use linguistic information such as character n grams or dictionaries to postprocess character recognition results These methods essentially discard the input image after the character recognition is complete This paper proposes a new technique for improving the performance of an OCR system that uses informa...

Speech recognition was measured as a function of spectral resolution (number of spectral channels) and speech-to-noise ratio in normal-hearing (NH) and cochlear-implant (CI) listeners. Vowel, consonant, word, and sentence recognition were measured in five normal-hearing listeners, ten listeners with the Nucleus-22 cochlear implant, and nine listeners with the Advanced Bionics Clarion cochlear i...

This paper addresses the problem of automatic speech recognition in the presence of interfering noise. It focuses on the Parallel Model Combination (PMC) scheme, which has been shown to be a powerful technique for achieving noise robustness. Most experiments reported on PMC to date have been on small, 10-50 word vocabulary systems. Experiments on the Resource Management (RM) database, a 1000 wo...

OBJECTIVES/HYPOTHESIS This study documents the importance of preserving residual low-frequency acoustic hearing as those with more residual hearing are selected for cochlear implantation. Surgical strategies used for hearing preservation with a short hybrid cochlear implant are outlined. The benefits of preserved residual low-frequency hearing, improved word understanding in noise, and music ap...

A two-part study examined recognition of speech produced in quiet and in noise by normal hearing adults. In Part I 5 women produced 50 sentences consisting of an ambiguous carrier phrase followed by a unique target word. These sentences were spoken in three environments: quiet, wide band noise (WBN), and meaningful multi-talker babble (MMB). The WBN and MMB competitors were presented through in...

This paper describes an approach to increase the noise robustness of automatic speech recognition systems by, transforming the signal after Mel scaled filtering, to make the cumulative density functions of the signal’s values in recognition match the ones that where estimated on the training data. The cumulative density functions are approximated using a small number of quantiles. Recognition t...

A blind dereverberation method based on power spectral subtraction (SS) using a multi-channel least mean squares algorithm was previously proposed to suppress the reverberant speech without additive noise. The results of isolated word speech recognition experiments showed that this method achieved significant improvements over conventional cepstral mean normalization (CMN) in a reverberant envi...

This paper discusses the problem of automatic word boundary detection in the presence of variable-level background noise in cars. Commonly used robust word boundary detection algorithms always assume that the background noise level is fixed and sets fixed thresholds to find the boundary of word signal. In fact, the background noise level in cars varies in the procedure of recording due to speed...