Learning static spectral weightings for speech intelligibility enhancement in noise

Near-end speech enhancement works by modifying speech prior to presentation in a noisy environment, typically operating under a constraint of limited or no increase in speech level. One issue is the extent to which near-end enhancement techniques require detailed estimates of the masking environment to function effectively. The current study investigated speech modification strategies based on reallocating energy statically across the spectrum using masker-specific spectral weightings. Weighting patterns were learned offline by maximising a glimpse-based objective intelligibility metric. Keyword scores in sentences in the presence of stationary and fluctuating maskers increased, in some cases by very substantial amounts, following the application of masker- and SNR-specific spectral weighting. A second experiment using generic masker-independent spectral weightings that boosted all frequencies above 1 kHz also led to significant gains in most conditions. These findings indicate that energy-neutral spectral weighting is a highly-effective near-end speech enhancement approach that places minimal demands on detailed masker estimation

A study on the relationship between the intelligibility and quality of algorithmically-modified speech for normal hearing listeners

This study investigates the relationship between the intelligibility and quality of modified speech in noise and in quiet. Speech signals were processed by seven algorithms designed to increase speech intelligibility in noise without altering speech intensity. In three noise maskers, including both stationary and fluctuating noise at two signal-to-noise ratios (SNR), listeners identified keywords from unmodified or modified sentences. The intelligibility performance of each type of speech was measured as the listeners’ word recognition rate in each condition, while the quality was rated as a mean opinion score. In quiet, only the perceptual quality of each type of speech was assessed. The results suggest that when listening in noise, modification performance on improving intelligibility is more important than its potential negative impact on speech quality. However, when listening in quiet or at SNRs in which intelligibility is no longer an issue to listeners, the impact to speech quality due to modification becomes a concern

How reliable are online speech intelligibility studies with known listener cohorts?

Although the use of nontraditional settings for speech perception experiments is growing, there have been few controlled comparisons of online and laboratory modalities in the context of speech intelligibility. The current study compares outcomes from three web-based replications of recent laboratory studies involving distorted, masked, fil- tered, and enhanced speech, amounting to 40 separate conditions. Rather than relying on unrestricted crowdsourcing, this study made use of participants from the population that would normally volunteer to take part physically in labo- ratory experiments. In sentence transcription tasks, the web cohort produced intelligibility scores 3–6 percentage points lower than their laboratory counterparts, and test modality interacted with experimental condition. These disparities and interactions largely disappeared after the exclusion of those web listeners who self-reported the use of low quality headphones, and the remaining listener cohort was also able to replicate key outcomes of each of the three laboratory studies. The laboratory and web modalities produced similar measures of experimental efficiency based on listener variability, response errors, and outlier counts. These findings suggest that the combination of known listener cohorts and moderate headphone quality provides a feasible alternative to traditional laboratory intel- ligibility studies.Basque Government Consolidados programme under Grant No. IT311-1

Listeners’ Spectral Reallocation Preferences for Speech in Noise

Modifying the spectrum of recorded or synthetic speech is an effective strategy for boosting intelligibility in noise without increasing the speech level. However, the wider impact of changes to the spectral energy distribution of speech is poorly understood. The present study explored the influence of spectral modifications using an experimental paradigm in which listeners were able to adjust speech parameters directly with real-time audio feedback, allowing the joint elicitation of preferences and word recognition scores. In two experiments involving full-bandwidth and bandwidth-limited speech, respectively, listeners adjusted one of eight features that altered the speech spectrum, and then immediately carried out a sentence-in-noise recognition task at the chosen setting. Listeners’ preferred adjustments in most conditions involved the transfer of speech energy from the sub-1 kHz region to the 1–4 kHz range. Preferences were not random, even when intelligibility was at the ceiling or constant across a range of adjustment values, suggesting that listener choices encompass more than a desire to maintain comprehensibility.Olympia Simantiraki was funded by the European Commission under the Marie Curie European Training Network ENRICH (675324)