Listening in large rooms : a neurophysiological investigations of acoustical conditions that influence speech intelligibility

Thesis (M.S.)--Massachusetts Institute of Technology, Whitaker College of Health Sciences and Technology, 1997.Includes bibliographical references (p. 34-37).by Benjamin Michael Hammond.M.S

Determination and evaluation of clinically efficient stopping criteria for the multiple auditory steady-state response technique

Background: Although the auditory steady-state response (ASSR) technique utilizes objective statistical detection algorithms to estimate behavioural hearing thresholds, the audiologist still has to decide when to terminate ASSR recordings introducing once more a certain degree of subjectivity. Aims: The present study aimed at establishing clinically efficient stopping criteria for a multiple 80-Hz ASSR system. Methods: In Experiment 1, data of 31 normal hearing subjects were analyzed off-line to propose stopping rules. Consequently, ASSR recordings will be stopped when (1) all 8 responses reach significance and significance can be maintained for 8 consecutive sweeps; (2) the mean noise levels were ≤ 4 nV (if at this “≤ 4-nV” criterion, p-values were between 0.05 and 0.1, measurements were extended only once by 8 sweeps); and (3) a maximum amount of 48 sweeps was attained. In Experiment 2, these stopping criteria were applied on 10 normal hearing and 10 hearing-impaired adults to asses the efficiency. Results: The application of these stopping rules resulted in ASSR threshold values that were comparable to other multiple-ASSR research with normal hearing and hearing-impaired adults. Furthermore, in 80% of the cases, ASSR thresholds could be obtained within a time-frame of 1 hour. Investigating the significant response-amplitudes of the hearing-impaired adults through cumulative curves indicated that probably a higher noise-stop criterion than “≤ 4 nV” can be used. Conclusions: The proposed stopping rules can be used in adults to determine accurate ASSR thresholds within an acceptable time-frame of about 1 hour. However, additional research with infants and adults with varying degrees and configurations of hearing loss is needed to optimize these criteria

Resource-efficient high-dimensional subspace teleportation with a quantum autoencoder.

Quantum autoencoders serve as efficient means for quantum data compression. Here, we propose and demonstrate their use to reduce resource costs for quantum teleportation of subspaces in high-dimensional systems. We use a quantum autoencoder in a compress-teleport-decompress manner and report the first demonstration with qutrits using an integrated photonic platform for future scalability. The key strategy is to compress the dimensionality of input states by erasing redundant information and recover the initial states after chip-to-chip teleportation. Unsupervised machine learning is applied to train the on-chip autoencoder, enabling the compression and teleportation of any state from a high-dimensional subspace. Unknown states are decompressed at a high fidelity (~0.971), obtaining a total teleportation fidelity of ~0.894. Subspace encodings hold great potential as they support enhanced noise robustness and increased coherence. Laying the groundwork for machine learning techniques in quantum systems, our scheme opens previously unidentified paths toward high-dimensional quantum computing and networking

Utilization of the chirp stimulus in auditory brainstem response measurements

Välittömästi äänistimulusta seuraavaa, aivorungosta lähtöisin olevaa sähköistä aktiviteettia kutsutaan auditoriseksi aivorunkovasteeksi (ABR, auditory brainstem response). ABR:ää käytetään laajalti kuulon objektiiviseen testaamiseen. Siinä missä perinteisessä äänesaudiometriassa koehenkilön tulee vastata testiääniin ennalta määrätyllä tavalla, ABR voidaan mitata ilman koehenkilön aktiivista osallistumista. Hiljattain ABR-mittauksia varten on kehitetty uudenlainen stimulus: chirp. Chirpin tarkoituksena on tuottaa suurempi ABR-amplitudi lisäämällä sisäkorvan karvasolujen aktiviteetin yhtäaikaisuutta. 1,5 - 2-kertaisia parannuksia onkin raportoitu verrattuna perinteisiin stimuluksiin. Tässä työssä perinteisiä click- ja tone burst -stimuluksia on vertailtu vastaaviin laajakaistaiseen chirpiin ja taajuusspesifeihin kapeakaistaisiin chirpeihin. ABR-kynnystasoja vertailtiin myös toisella objektiivisella metodilla, ASSR:llä saatuihin kynnystasoihin. Vasteet mitattiin kuudelta normaalikuuloiselta ja viideltä huonokuuloiselta koehenkilöltä Interacousticsin Eclipse-järjestelmällä. Perinteisten ja chirp-stimulusten eroja tutkittiin vertailemalla normaalikuuloisilta mitattujen vasteiden amplitudeja. Myös kaikilta koehenkilöiltä mitattuja kynnysarvoja verrattiin äänesaudiometrialla määriteltyihin kuulokynnyksiin. Tulosten perusteella perinteisten stimulusten ja vastaavien chirp stimulusten välillä ei löytynyt tilastollisesti merkitseviä eroja. ASSR- ja ABR-kynnysarvojen luotettava vertailu ei myöskään ollut mahdollista johtuen saatujen kynnysarvojen pienestä määrästä. Johtopäätöksissä todettiin, että tuloksiin on todennäköisesti vaikuttanut tutkimuksessa käytettyjen kuulokkeiden tyyppi. Aiemmissa, chirpin paremmuuden kannalla olleissa tutkimuksissa, mittaukset tehtiin käyttäen toista kuulokemallia. Myös kuulonaleneman vaikutukset chirp stimuluksella suoritettuihin ABR-mittauksiin ovat huonosti tunnettuja, antaen aihetta jatkotutkimuksille.The electrical activity originating from the auditory structures of the brainstem is called the auditory brainstem response (ABR). The ABR is used widely for objective assessment of the hearing system. Whereas traditional pure tone audiometry requires the test subject to respond to probe tones in a predefined manner, the ABR can be recorded without any active participation of the subject. Recently, a new kind of stimulus has been developed for ABR measurements. This stimulus, called chirp, aims at increasing the ABR amplitude by promoting synchronous firing of the hair cells in the inner ear. 1,5 - 2 times higher ABR amplitudes have indeed been recorded using the chirp when compared to traditional stimuli. In this thesis, traditional click and tone burst stimuli were compared to corresponding chirp variants; the broadband chirp and frequency-specific narrowband chirps. Also, the ABR results were compared to those obtained by another objective method, the auditory steady-state response (ASSR). Responses were obtained from six normal-hearing subjects and five hard-of-hearing subjects using the Eclipse platform from Interacoustics. In normal-hearing subjects, the ABR amplitudes were compared between traditional and chirp stimuli. In all subjects, ABR and ASSR thresholds were compared to the behavioral thresholds. Results failed to show significant differences between traditional stimuli and corresponding chirp variants. Also, comparison of and ASSR thresholds could not be done reliably because of the small number of obtained thresholds. It was concluded that the results were influenced by the type of the insert earphones used in this study. Previous results in favour of the chirp have been obtained using a different type of earphones. Also, it was suggested that the influence of hearing loss on chirp-elicited ABRs be investigated in the future

Hooked on Music Information Retrieval

This article provides a reply to 'Lure(d) into listening: The potential of cognition-based music information retrieval,' in which Henkjan Honing discusses the potential impact of his proposed Listen, Lure & Locate project on Music Information Retrieval (MIR). Honing presents some critical remarks on data-oriented approaches in MIR, which we endorse. To place these remarks in context, we first give a brief overview of the state of the art of MIR research. Then we present a series of arguments that show why purely data-oriented approaches are unlikely to take MIR research and applications to a more advanced level. Next, we propose our view on MIR research, in which the modelling of musical knowledge has a central role. Finally, we elaborate on the ideas in Honing's paper from a MIR perspective in this paper and propose some additions to the Listen, Lure & Locate project

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Computational Models of Representation and Plasticity in the Central Auditory System

The performance for automated speech processing tasks like speech recognition and speech activity detection rapidly degrades in challenging acoustic conditions. It is therefore necessary to engineer systems that extract meaningful information from sound while exhibiting invariance to background noise, different speakers, and other disruptive channel conditions. In this thesis, we take a biomimetic approach to these problems, and explore computational strategies used by the central auditory system that underlie neural information extraction from sound. In the first part of this thesis, we explore coding strategies employed by the central auditory system that yield neural responses that exhibit desirable noise robustness. We specifically demonstrate that a coding strategy based on sustained neural firings yields richly structured spectro-temporal receptive fields (STRFs) that reflect the structure and diversity of natural sounds. The emergent receptive fields are comparable to known physiological neuronal properties and can be employed as a signal processing strategy to improve noise invariance in a speech recognition task. Next, we extend the model of sound encoding based on spectro-temporal receptive fields to incorporate the cognitive effects of selective attention. We propose a framework for modeling attention-driven plasticity that induces changes to receptive fields driven by task demands. We define a discriminative cost function whose optimization and solution reflect a biologically plausible strategy for STRF adaptation that helps listeners better attend to target sounds. Importantly, the adaptation patterns predicted by the framework have a close correspondence with known neurophysiological data. We next generalize the framework to act on the spectro-temporal dynamics of task-relevant stimuli, and make predictions for tasks that have yet to be experimentally measured. We argue that our generalization represents a form of object-based attention, which helps shed light on the current debate about auditory attentional mechanisms. Finally, we show how attention-modulated STRFs form a high-fidelity representation of the attended target, and we apply our results to obtain improvements in a speech activity detection task. Overall, the results of this thesis improve our general understanding of central auditory processing, and our computational frameworks can be used to guide further studies in animal models. Furthermore, our models inspire signal processing strategies that are useful for automated speech and sound processing tasks