The performance of speech recognizers deteriorates in case of a mismatch between the conditions during training and recognition. One difference is the presence of a stationary background noise during recognition which is also referred to as “additive” noise. Furthermore the recognition is influenced by the frequency response of the whole transmission channel from the speaker to the audio input ...

Widely Speech Signal Processing has not been used much in the field of electronics and computers due to the complexity and variety of speech signals and sounds with the advent of new technology. However, with modern processes, algorithms, and methods which can proc Demand for speech recognition technology is expected to their mobile phones as all purpose lifestyle devices. In this paper, an imp...

PURPOSE The purpose of this study was to determine if patient characteristics or clinical variables could predict who benefits from individual auditory training. METHOD A retrospective series of analyses were performed using a data set from a large, multisite, randomized controlled clinical trial that compared the treatment effects of at-home auditory training programs in bilateral hearing ai...

Speech comprehension is resistant to acoustic distortion in the input, reflecting listeners' ability to adjust perceptual processes to match the speech input. This adjustment is reflected in improved comprehension of distorted speech with experience. For noise vocoding, a manipulation that removes spectral detail from speech, listeners' word report showed a significantly greater improvement ove...

This article proposes offline language-free writer identification based on speeded-up robust features (SURF), goes through training, enrollment, and identification stages. In all stages, an isotropic Box filter is first used to segment the handwritten text image into word regions (WRs). Then, the SURF descriptors (SUDs) of word region and the corresponding scales and orientations (SOs) are extr...

It is indispensable to establish an objective test methodology for noise-reduced speech. This paper proposes a new methodology which estimates word intelligibility of the noise-reduced speech from PESQ MOS (subjective MOS estimated by the PESQ). To evaluate the effectiveness of the proposed methodology, a word intelligibility test of the noise-reduced speech was performed by using four noise re...

We propose a novel framework for noise robust automatic speech recognition (ASR) based on cochlear implant-like spectrally reduced speech (SRS). Two experimental protocols (EPs) are proposed in order to clarify the advantage of using SRS for noise robust ASR. These two EPs assess the SRS in both the training and testing environments. Speech enhancement was used in one of two EPs to improve the ...

In this study, discriminative HMM training and its performance are investigated in both clean and noisy environments. Recognition error is defined at string, word, phone, and acoustic levels and treated in a unified framework in discriminative training. With an acoustic level, high-resolution error measurement, a discriminative criterion of minimum divergence (MD) is proposed. Using speaker-ind...