Acoustic Speaker Localization with Strong Reverberation and Adaptive Feature Filtering with a Bayes RFS Framework

The thesis investigates the challenges of speaker localization in presence of strong reverberation, multi-speaker tracking, and multi-feature multi-speaker state filtering, using sound recordings from microphones. Novel reverberation-robust speaker localization algorithms are derived from the signal and room acoustics models. A multi-speaker tracking filter and a multi-feature multi-speaker state filter are developed based upon the generalized labeled multi-Bernoulli random finite set framework. Experiments and comparative studies have verified and demonstrated the benefits of the proposed methods

An exploratory investigation of speech recognition thresholds in noise with auralisations of two reverberant rooms

Objective Speech-in-noise tests are widely used in hearing diagnostics but typically without reverberation, although reverberation is an inextricable part of everyday listening conditions. To support the development of more real-life-like test paradigms, the objective of this study was to explore how spatially reproduced reverberation affects speech recognition thresholds in normal-hearing and hearing-impaired listeners. Design Thresholds were measured with a Finnish speech-in-noise test without reverberation and with two test conditions with reverberation times of similar to 0.9 and 1.8 s. Reverberant conditions were produced with a multichannel auralisation technique not used before in this context. Study sample Thirty-four normal-hearing and 14 hearing-impaired listeners participated in this study. Five people were tested with and without hearing aids. Results No significant differences between test conditions were found for the normal-hearing listeners. Results for the hearing-impaired listeners indicated better performance for the 0.9 s reverberation time compared to the reference and the 1.8 s conditions. Benefit from hearing aid use varied between individuals; for one person, an advantage was observed only with reverberation. Conclusions Auralisations may offer information on speech recognition performance that is not obtained with a test without reverberation. However, more complex stimuli and/or higher signal-to-noise ratios should be used in the future.Peer reviewe

Acoustic Properties of Absorbing Materials

Thanks to the progress made in materials research and to the introduction of innovative manufacturing technologies, a wide range of sound-absorbing elements are currently available to adjust the acoustic features of an environment. Nowadays, performance is only one of the required specifications, together with environmental compatibility, longevity, and affordable cost. This book collects the most recent advances in the broad-spectrum characterization of sound-absorbing materials used in civil, industrial, and tertiary applications, by means of experimental, numerical, or theoretical studies