In this research various objective quality measures are evaluated in order to predict the intelligibility for a wide range of non-linearly processed speech signals and speech degraded by additive noise. The obtained results are compared with the prediction results of a more advanced perceptual-based model proposed by Dau et al. and an objective intelligibility measure, namely the coherence spee...

The purpose of this study was to improve the speech processing strategy for cochlear implants (CIs) A speech preprocessing algorithm is presented to improve the speech intelligibility in noise. The algorithm improves the intelligibility by optimally redistributing the speech energy over time and frequency for a perceptual distortion measure, the algorithm is more sensitive to transient regions....

Instrumental measures of speech intelligibility typically produce an index between 0 and 1 that is monotonically related to listening test scores. As such, these measures are dimensionless and do not represent physical quantities. In this paper, we propose a new instrumental intelligibility metric that describes speech intelligibility using bits per second. The proposed metric builds upon an ex...

PURPOSE The authors examined speech intelligibility in typically developing (TD) children and 3 groups of children with cerebral palsy (CP) who were classified into speech/language profile groups following Hustad, Gorton, and Lee (2010). Questions addressed differences in transcription intelligibility scores among groups, the effects of utterance length on intelligibility, the relationship betw...

Intelligibility is generally accepted to be a very relevant measure in the assessment of pathological speech. In clinical practice, intelligibility is measured using one of the many existing perceptual tests. These tests usually have the drawback that they employ unnatural speech material (e.g. nonsense words) and that they cannot fully exclude errors due to the listener's bias. This raises the...

A higher intelligibility subspace speech-enhancement algorithm based on a theoretical upper bound on the gain function is proposed. The majority existing speech-enhancement algorithms cannot effectively improve enhanced speech intelligibility. One important reason is that they only use Minimum Mean Square Error (MMSE) to constrain speech distortion but ignore that speech distortion region diffe...

Speech intelligibility is an important factor for successful speech communication in today’s society. So-called near-end listening enhancement (NELE) algorithms aim at improving speech intelligibility in conditions where the (clean) speech signal is accessible and can be modified prior to its presentation. However, many of these algorithms only consider the detrimental effect of noise and disre...

The noise influence to speech signal waveform can be characterized by reduced speech dynamic range (rDR). This motivated the present work to propose an rDR-based intelligibility measure (denoted as rDRm) that could be used to non-intrusively (i.e., do not require clean reference speech signal) predict speech intelligibility in noise and is computed only using the dynamic range extracted from th...

the speech enhancement techniques are often employed to improve the quality and intelligibility of the noisy speech signals. this paper discusses a novel technique for speech enhancement which is based on singular value decomposition. this implementation utilizes a genetic algorithm based optimization method for reducing the effects of environmental noises from the singular vectors as well as t...