Auf einem menschlichen Gehörmodell basierende Elektrodenstimulationsstrategie für Cochleaimplantate

Cochleaimplantate (CI), verbunden mit einer professionellen Rehabilitation, haben mehreren hunderttausenden Hörgeschädigten die verbale Kommunikation wieder ermöglicht. Betrachtet man jedoch die Rehabilitationserfolge, so haben CI-Systeme inzwischen ihre Grenzen erreicht. Die Tatsache, dass die meisten CI-Träger nicht in der Lage sind, Musik zu genießen oder einer Konversation in geräuschvoller Umgebung zu folgen, zeigt, dass es noch Raum für Verbesserungen gibt.Diese Dissertation stellt die neue CI-Signalverarbeitungsstrategie Stimulation based on Auditory Modeling (SAM) vor, die vollständig auf einem Computermodell des menschlichen peripheren Hörsystems beruht.Im Rahmen der vorliegenden Arbeit wurde die SAM Strategie dreifach evaluiert: mit vereinfachten Wahrnehmungsmodellen von CI-Nutzern, mit fünf CI-Nutzern, und mit 27 Normalhörenden mittels eines akustischen Modells der CI-Wahrnehmung. Die Evaluationsergebnisse wurden stets mit Ergebnissen, die durch die Verwendung der Advanced Combination Encoder (ACE) Strategie ermittelt wurden, verglichen. ACE stellt die zurzeit verbreitetste Strategie dar. Erste Simulationen zeigten, dass die Sprachverständlichkeit mit SAM genauso gut wie mit ACE ist. Weiterhin lieferte SAM genauere binaurale Merkmale, was potentiell zu einer Verbesserung der Schallquellenlokalisierungfähigkeit führen kann. Die Simulationen zeigten ebenfalls einen erhöhten Anteil an zeitlichen Pitchinformationen, welche von SAM bereitgestellt wurden. Die Ergebnisse der nachfolgenden Pilotstudie mit fünf CI-Nutzern zeigten mehrere Vorteile von SAM auf. Erstens war eine signifikante Verbesserung der Tonhöhenunterscheidung bei Sinustönen und gesungenen Vokalen zu erkennen. Zweitens bestätigten CI-Nutzer, die kontralateral mit einem Hörgerät versorgt waren, eine natürlicheren Klangeindruck. Als ein sehr bedeutender Vorteil stellte sich drittens heraus, dass sich alle Testpersonen in sehr kurzer Zeit (ca. 10 bis 30 Minuten) an SAM gewöhnen konnten. Dies ist besonders wichtig, da typischerweise Wochen oder Monate nötig sind. Tests mit Normalhörenden lieferten weitere Nachweise für die verbesserte Tonhöhenunterscheidung mit SAM.Obwohl SAM noch keine marktreife Alternative ist, versucht sie den Weg für zukünftige Strategien, die auf Gehörmodellen beruhen, zu ebnen und ist somit ein erfolgversprechender Kandidat für weitere Forschungsarbeiten.Cochlear implants (CIs) combined with professional rehabilitation have enabled several hundreds of thousands of hearing-impaired individuals to re-enter the world of verbal communication. Though very successful, current CI systems seem to have reached their peak potential. The fact that most recipients claim not to enjoy listening to music and are not capable of carrying on a conversation in noisy or reverberative environments shows that there is still room for improvement.This dissertation presents a new cochlear implant signal processing strategy called Stimulation based on Auditory Modeling (SAM), which is completely based on a computational model of the human peripheral auditory system.SAM has been evaluated through simplified models of CI listeners, with five cochlear implant users, and with 27 normal-hearing subjects using an acoustic model of CI perception. Results have always been compared to those acquired using Advanced Combination Encoder (ACE), which is today’s most prevalent CI strategy. First simulations showed that speech intelligibility of CI users fitted with SAM should be just as good as that of CI listeners fitted with ACE. Furthermore, it has been shown that SAM provides more accurate binaural cues, which can potentially enhance the sound source localization ability of bilaterally fitted implantees. Simulations have also revealed an increased amount of temporal pitch information provided by SAM. The subsequent pilot study, which ran smoothly, revealed several benefits of using SAM. First, there was a significant improvement in pitch discrimination of pure tones and sung vowels. Second, CI users fitted with a contralateral hearing aid reported a more natural sound of both speech and music. Third, all subjects were accustomed to SAM in a very short period of time (in the order of 10 to 30 minutes), which is particularly important given that a successful CI strategy change typically takes weeks to months. An additional test with 27 normal-hearing listeners using an acoustic model of CI perception delivered further evidence for improved pitch discrimination ability with SAM as compared to ACE.Although SAM is not yet a market-ready alternative, it strives to pave the way for future strategies based on auditory models and it is a promising candidate for further research and investigation

Processing complex sounds passing through the rostral brainstem : The new early filter model

The rostral brainstem receives both “bottom-up” input from the ascending auditory system and “top-down” descending corticofugal connections. Speech information passing through the inferior colliculus of elderly listeners reflects the periodicity envelope of a speech syllable. This information arguably also reflects a composite of temporal-fine-structure (TFS) information from the higher frequency vowel harmonics of that repeated syllable. The amplitude of those higher frequency harmonics, bearing high frequency TFS information, correlates positively with the word recognition ability of elderly listeners under reverberatory conditions. Also relevant is that working memory capacity, which is subject to age-related decline, constrains the processing of sounds at the level of the brainstem. Turning to the effects of a visually presented sensory or memory load on auditory processes, there is a load-dependent reduction of that processing, as manifest in the auditory brainstem responses evoked by to-be-ignored clicks. Wave V decreases in amplitude with increases in the visually presented memory load. A visually presented sensory load also produces a load-dependent reduction of a slightly different sort: The sensory load of visually presented information limits the disruptive effects of background sound upon working memory performance. A new early filter model is thus advanced whereby systems within the frontal lobe (affected by sensory or memory load) cholinergically influence top-down corticofugal connections. Those corticofugal connections constrain the processing of complex sounds such as speech at the level of the brainstem. Selective attention thereby limits the distracting effects of background sound entering the higher auditory system via the inferior colliculus. Processing TFS in the brainstem relates to perception of speech under adverse conditions. Attentional selectivity is crucial when the signal heard is degraded or masked: e.g., speech in noise, speech in reverberatory environments. The assumptions of a new early filter model are consistent with these findings: A subcortical early filter, with a predictive selectivity based on acoustical (linguistic) context and foreknowledge, is under cholinergic top-down control. A limited prefrontal capacity limitation constrains this top-down control as is guided by the cholinergic processing of contextual information in working memory.Peer reviewe

An investigation of the utility of monaural sound source separation via nonnegative matrix factorization applied to acoustic echo and reverberation mitigation for hands-free telephony

In this thesis we investigate the applicability and utility of Monaural Sound Source Separation (MSSS) via Nonnegative Matrix Factorization (NMF) for various problems related to audio for hands-free telephony. We first investigate MSSS via NMF as an alternative acoustic echo reduction approach to existing approaches such as Acoustic Echo Cancellation (AEC). To this end, we present the single-channel acoustic echo problem as an MSSS problem, in which the objective is to extract the users signal from a mixture also containing acoustic echo and noise. To perform separation, NMF is used to decompose the near-end microphone signal onto the union of two nonnegative bases in the magnitude Short Time Fourier Transform domain. One of these bases is for the spectral energy of the acoustic echo signal, and is formed from the in- coming far-end user’s speech, while the other basis is for the spectral energy of the near-end speaker, and is trained with speech data a priori. In comparison to AEC, the speaker extraction approach obviates Double-Talk Detection (DTD), and is demonstrated to attain its maximal echo mitigation performance immediately upon initiation and to maintain that performance during and after room changes for similar computational requirements. Speaker extraction is also shown to introduce distortion of the near-end speech signal during double-talk, which is quantified by means of a speech distortion measure and compared to that of AEC. Subsequently, we address Double-Talk Detection (DTD) for block-based AEC algorithms. We propose a novel block-based DTD algorithm that uses the available signals and the estimate of the echo signal that is produced by NMF-based speaker extraction to compute a suitably normalized correlation-based decision variable, which is compared to a fixed threshold to decide on doubletalk. Using a standard evaluation technique, the proposed algorithm is shown to have comparable detection performance to an existing conventional block-based DTD algorithm. It is also demonstrated to inherit the room change insensitivity of speaker extraction, with the proposed DTD algorithm generating minimal false doubletalk indications upon initiation and in response to room changes in comparison to the existing conventional DTD. We also show that this property allows its paired AEC to converge at a rate close to the optimum. Another focus of this thesis is the problem of inverting a single measurement of a non- minimum phase Room Impulse Response (RIR). We describe the process by which percep- tually detrimental all-pass phase distortion arises in reverberant speech filtered by the inverse of the minimum phase component of the RIR; in short, such distortion arises from inverting the magnitude response of the high-Q maximum phase zeros of the RIR. We then propose two novel partial inversion schemes that precisely mitigate this distortion. One of these schemes employs NMF-based MSSS to separate the all-pass phase distortion from the target speech in the magnitude STFT domain, while the other approach modifies the inverse minimum phase filter such that the magnitude response of the maximum phase zeros of the RIR is not fully compensated. Subjective listening tests reveal that the proposed schemes generally produce better quality output speech than a comparable inversion technique

An investigation of the utility of monaural sound source separation via nonnegative matrix factorization applied to acoustic echo and reverberation mitigation for hands-free telephony

In this thesis we investigate the applicability and utility of Monaural Sound Source Separation (MSSS) via Nonnegative Matrix Factorization (NMF) for various problems related to audio for hands-free telephony. We first investigate MSSS via NMF as an alternative acoustic echo reduction approach to existing approaches such as Acoustic Echo Cancellation (AEC). To this end, we present the single-channel acoustic echo problem as an MSSS problem, in which the objective is to extract the users signal from a mixture also containing acoustic echo and noise. To perform separation, NMF is used to decompose the near-end microphone signal onto the union of two nonnegative bases in the magnitude Short Time Fourier Transform domain. One of these bases is for the spectral energy of the acoustic echo signal, and is formed from the in- coming far-end user’s speech, while the other basis is for the spectral energy of the near-end speaker, and is trained with speech data a priori. In comparison to AEC, the speaker extraction approach obviates Double-Talk Detection (DTD), and is demonstrated to attain its maximal echo mitigation performance immediately upon initiation and to maintain that performance during and after room changes for similar computational requirements. Speaker extraction is also shown to introduce distortion of the near-end speech signal during double-talk, which is quantified by means of a speech distortion measure and compared to that of AEC. Subsequently, we address Double-Talk Detection (DTD) for block-based AEC algorithms. We propose a novel block-based DTD algorithm that uses the available signals and the estimate of the echo signal that is produced by NMF-based speaker extraction to compute a suitably normalized correlation-based decision variable, which is compared to a fixed threshold to decide on doubletalk. Using a standard evaluation technique, the proposed algorithm is shown to have comparable detection performance to an existing conventional block-based DTD algorithm. It is also demonstrated to inherit the room change insensitivity of speaker extraction, with the proposed DTD algorithm generating minimal false doubletalk indications upon initiation and in response to room changes in comparison to the existing conventional DTD. We also show that this property allows its paired AEC to converge at a rate close to the optimum. Another focus of this thesis is the problem of inverting a single measurement of a non- minimum phase Room Impulse Response (RIR). We describe the process by which percep- tually detrimental all-pass phase distortion arises in reverberant speech filtered by the inverse of the minimum phase component of the RIR; in short, such distortion arises from inverting the magnitude response of the high-Q maximum phase zeros of the RIR. We then propose two novel partial inversion schemes that precisely mitigate this distortion. One of these schemes employs NMF-based MSSS to separate the all-pass phase distortion from the target speech in the magnitude STFT domain, while the other approach modifies the inverse minimum phase filter such that the magnitude response of the maximum phase zeros of the RIR is not fully compensated. Subjective listening tests reveal that the proposed schemes generally produce better quality output speech than a comparable inversion technique

Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication

A new theory of mammalian hearing is presented, which accounts for the auditory image in the midbrain (inferior colliculus) of objects in the acoustical environment of the listener. It is shown that the ear is a temporal imaging system that comprises three transformations of the envelope functions: cochlear group-delay dispersion, cochlear time lensing, and neural group-delay dispersion. These elements are analogous to the optical transformations in vision of diffraction between the object and the eye, spatial lensing by the lens, and second diffraction between the lens and the retina. Unlike the eye, it is established that the human auditory system is naturally defocused, so that coherent stimuli do not react to the defocus, whereas completely incoherent stimuli are impacted by it and may be blurred by design. It is argued that the auditory system can use this differential focusing to enhance or degrade the images of real-world acoustical objects that are partially coherent. The theory is founded on coherence and temporal imaging theories that were adopted from optics. In addition to the imaging transformations, the corresponding inverse-domain modulation transfer functions are derived and interpreted with consideration to the nonuniform neural sampling operation of the auditory nerve. These ideas are used to rigorously initiate the concepts of sharpness and blur in auditory imaging, auditory aberrations, and auditory depth of field. In parallel, ideas from communication theory are used to show that the organ of Corti functions as a multichannel phase-locked loop (PLL) that constitutes the point of entry for auditory phase locking and hence conserves the signal coherence. It provides an anchor for a dual coherent and noncoherent auditory detection in the auditory brain that culminates in auditory accommodation. Implications on hearing impairments are discussed as well.Comment: 603 pages, 131 figures, 13 tables, 1570 reference

Ultra-high-speed imaging of bubbles interacting with cells and tissue

Ultrasound contrast microbubbles are exploited in molecular imaging, where bubbles are directed to target cells and where their high-scattering cross section to ultrasound allows for the detection of pathologies at a molecular level. In therapeutic applications vibrating bubbles close to cells may alter the permeability of cell membranes, and these systems are therefore highly interesting for drug and gene delivery applications using ultrasound. In a more extreme regime bubbles are driven through shock waves to sonoporate or kill cells through intense stresses or jets following inertial bubble collapse. Here, we elucidate some of the underlying mechanisms using the 25-Mfps camera Brandaris128, resolving the bubble dynamics and its interactions with cells. We quantify acoustic microstreaming around oscillating bubbles close to rigid walls and evaluate the shear stresses on nonadherent cells. In a study on the fluid dynamical interaction of cavitation bubbles with adherent cells, we find that the nonspherical collapse of bubbles is responsible for cell detachment. We also visualized the dynamics of vibrating microbubbles in contact with endothelial cells followed by fluorescent imaging of the transport of propidium iodide, used as a membrane integrity probe, into these cells showing a direct correlation between cell deformation and cell membrane permeability