A new algorithm has been developed to achieve the separation of desired speech from interfering speech reverberating in a room. The algorithm is developed by viewing this problem as a two-data channel adaptive noise cancellation problem. Using a least squares error criteria in the adaptive noise canceler approach leads to classical system identification problem. The solution estimates the room ...

Overlapping speech is still a major cause of error in many speech processing applications, currently without any satisfactory solution. This paper considers the problem of detecting segments of overlapping speech within meeting recordings. Using an HMM-based framework recordings are segmented into intervals containing non-speech, speech and overlapping speech. New to this contribution is the us...

Speech separation is the task of separating target speech from background interference. Traditionally, speech separation is studied as a signal processing problem. A more recent approach formulates speech separation as a supervised learning problem, where the discriminative patterns of speech, speakers, and background noise are learned from training data. Over the past decade, many supervised s...

Speech dereverberation is desirable with a view to achieving, for example, robust speech recognition in the real world. However, it is still a challenging problem, especially when using a single microphone. Although blind equalization techniques have been exploited, they cannot deal with speech signals appropriately because their assumptions are not satisfied by speech signals. We propose a new...

The serial order problem is the problem of how any animal controls action sequences. Lashley maintained that in the case of speech the order of sounds was externally imposed on units that had, in themselves, no temporal valences. Speech errors reveal that the external source of control is a syllable structure (or frame) constraint on the placement of consonants and vowels (content elements) whe...

in this paper, genetic programming is applied for quality improvement of noisy speech signal. therefore, a system including both spectral subtraction and genetic programming is implemented for speech enhancement. in the proposed method, first noise is reduced by spectral subtraction. in the next step, genetic programming trees are trained for more enhancement of noisy signal by mapping the sign...

this study was an attempt to shed light on the use of requestive speech act by iranian nonnative speakers (nnss) of english and canadian native speakers (nss) of english to find out the (possible) similarities and/or differences between the request realizations, and to investigate the influence of the situational variables of power, distance, context familiarity, and l1’s (possible) influence. ...

This paper deals with the problem of building HMMs suitable for fast speech. Fast speech leads to increased error rates on various tasks. In the first part of the paper an automatic procedure is presented to split speech material into different categories according to the speaking rate, which is fundamental for all investigations on the speaking rate. In the second part the problem of sparse da...

Automatic speech recognition is critical in natural human-centric interfaces for ambient intelligence. The performance of an automatic speech recognition system, however, degrades drastically when there is a mismatch between training and testing conditions. The aim of robust speech recognition is to overcome the mismatch problem so the result is a moderate and graceful degradation in recognitio...