In this paper, we evaluate the performance of several state-of-the-art objective measures in terms of predicting speech intelligibility in Mandarin of the processed noisy signals by speech enhancement algorithms. The speech signals were first corrupted by three types of noises at two signal-to-noise ratios, followed by four classes of speech enhancement algorithms. The objective intelligibility...

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...

There are several tests of speech intelligibility currently available which employ a variety of methods. The most appropriate method for testing intelligibility of speech transmitted via telephony is a forced choice task in which listeners hear speech samples and identify what they hear from among a set of alternatives displayed onscreen. This methodology allows tests to be run quickly and scor...

To assess the link between accent and intelligibility, previous research has heavily relied on human responses, demonstrating that human assessment is influenced by such subjective factors as linguistic proficiency (Pihko, 1997), familiarity (Smith, 1992), age (Burda, 2000), reactions to speakers’ kinetic cues (Bara, 1992; Rubin, 1992), and dialectal differences (Smith & Bisazza, 1982). In part...

A distortion-weighted glimpsing metric developed for estimating monaural speech intelligibility is extended to predict binaural speech intelligibility in noise. Two aspects of binaural listening, the better ear effect and the binaural advantage, are taken into account in the new metric, which predicts intelligibility using monaural target and masker signals and their location, and is therefore ...

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...

Intelligibility of speech in adverse near-end noise conditions can be enhanced with post-processing. Recently, a postprocessing method based on statistical mapping of the spectral tilt of normal speech to that of Lombard speech was proposed. However, previous intelligibility improvement studies utilizing Lombard speech have mainly gathered data from read sentences which might result in a less p...

Current evidence demonstrates that even though some non-native listeners can achieve native-like performance for speech perception tasks in quiet, the presence of a background noise is much more detrimental to speech intelligibility for non-native compared to native listeners. Even when performance is equated across groups, it is likely that greater listening effort is required for non-native l...

The de-facto standard for dysarthric intelligibility assessment is a subjective intelligibility test, performed by an expert. Subjective tests are often costly, biased and inconsistent because of their perceptual nature. Automatic objective assessment methods, in contrast, are repeatable and relatively cheap. Objective methods can be broken down into two subcategories: reference-free, and refer...