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...

A study is presented on how well objective measures of speech quality and intelligibility can predict the subjective intelligibility of speech that has undergone spectral envelope smoothing and simplification of its excitation. Speech modifications are made by resynthesising speech that has been spectrally smoothed. Objective measures are applied to the modified speech and include measures of s...

Background: the reduction in speech intelligibility is considered one of the main characteristics of individuals with speech disorders, and is an important issue for clinical and research investigation. In spite of its relevance, the literature does not present a consensus on how to measure speech intelligibility. Besides the diversity of existent methods, another important issue refers to 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...

Recent literature indicates increasing interest in deep neural networks for use in speech enhancement systems. Currently, these systems are mostly evaluated through objective measures of speech quality and/or intelligibility. Subjective intelligibility evaluations of these systems have so far not been reported. In this paper we report the results of a speech recognition test with 15 participant...

A speech pre-processing algorithm is presented that improves the speech intelligibility in noise for the near-end listener. The algorithm improves intelligibility by optimally redistributing the speech energy over time and frequency according to a perceptual distortion measure, which is based on a spectro-temporal auditory model. Since this auditory model takes into account shorttime informatio...

Most current techniques for near-end speech intelligibility enhancement have focused on processing clean input signals, however, in realistic environments, the input is often noisy. Processing noisy speech for intelligibility enhancement using algorithms developed for clean signals can lower the perceptual quality of the samples when they are listened in quiet. Here we address the quality loss ...

In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...

In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...

In adverse listening conditions, talkers can increase their intelligibility by speaking clearly [Picheny, M.A., et al. (1985). J. Speech Hear. Res. 28, 96-103; Payton, K. L., et al. (1994). J. Acoust. Soc. Am. 95, 1581-1592]. This modified speaking style, known as clear speech, is typically spoken more slowly than conversational speech [Picheny, M. A., et al. (1986). J. Speech Hear. Res. 29, 43...