| 1. |
- Berninger, Erik, et al.
(författare)
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Analysis of Click-Evoked Auditory Brainstem Responses Using Time Domain Cross-Correlations Between Interleaved Responses
- 2014
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Ingår i: Ear and Hearing. - : Ovid Technologies (Wolters Kluwer Health). - 0196-0202 .- 1538-4667. ; 35:3, s. 318-329
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: The rapidly evolving field of early diagnostics after the introduction of newborn hearing screening requires rapid, valid, and objective methods, which have to be thoroughly evaluated in adults before use in infants. The aim was to study cross-correlation analysis of interleaved auditory brainstem responses (ABRs) in a wide dynamic range in normal-hearing adults. Off-line analysis allowed for comparison with psychoacoustical click threshold (PCT), pure-tone threshold, and determination of ABR input/output function. Specifically, nonfiltered and band-pass filtered ABRs were studied in various time segments along with time elapsed for ensemble of sweeps reaching a specific detection criterion. Design: Fourteen healthy normal-hearing subjects (18 to 35 years of age, 50% females) without any history of noise exposure participated. They all had pure-tone thresholds better than 20 dB HL (125 to 8000 Hz). ABRs were recorded in both ears using 100 sec clicks, from 71.5 dB nHL down to -18.5 dB nHL, in 10 dB steps (repetition rate, 39 Hz; time window, 15 msec; filter, 30 to 8000 Hz). The number of sweeps increased from 2000 at 71.5 dB nHL, up to 30000 at -18.5 dB nHL. Each sweep was stored in a data base for off-line analysis. Cross-correlation analysis between two subaverages of interleaved responses was performed in the time domain for nonfiltered and digitally band-pass filtered (300 to 1500 Hz) entire and time-windowed (1 to 11 and 5 to 11 msec) responses. PCTs were measured using a Bekesy technique with the same insert phone and stimulus as used for the ABR (repetition rate, 20 Hz). Time elapsed (approximate to number of accepted sweeps/repetition rate) for the ensemble of sweeps needed to reach a cross-correlation coefficient () of 0.70 (=3.7 dB signal-to-noise ratio [SNR]) was analyzed. Results: Mean cross-correlation coefficients exceeded 0.90 in both ears at stimulus levels 11.5 dB nHL for the entire nonfiltered ABR. At 1.5 dB nHL, mean(SD) was 0.53(0.32) and 0.44(0.40) for left and right ears, respectively (n = 14) (=0 dB SNR). In comparison, mean(SD) PCT was -1.9(2.9) and -2.5(3.2) dB nHL for left and right ears, respectively (n = 14), while mean pure-tone average (500 to 2000 Hz) was 2.5 dB HL (n = 28). Almost no effect of band-pass filtering or reduced analysis time window existed. Average time elapsed needed to reach = 0.70 was approximately 20 seconds or less at stimulus levels 41.5 dB nHL, and approximate to 30 seconds at 31.5 dB nHL. The average (interpolated) stimulus level corresponding to =0.70 for the entire nonfiltered ABR was 6.5 dB nHL (n = 28), which coincided with the estimated psychoacoustical threshold for single clicks. Conclusions: ABR could be identified in a short period of time using cross-correlation analysis between interleaved responses. The average stimulus level corresponding to 0 dB SNR in the entire nonfiltered ABR occurred at 1.5 dB nHL, 4 dB above the average PCT. The mean input/output function for the ensemble of sweeps required to reach = 0.70 increased monotonically with increasing stimulus level, in parallel with the ABR based on all sweeps (1.5 dB nHL). Time domain cross-correlation analysis of ABR might form the basis for automatic response identification and future threshold-seeking procedures.
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| 2. |
- Dahlquist, M., et al.
(författare)
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Methodology for quantifying perceptual effects from noise suppression systems
- 2005
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Ingår i: International Journal of Audiology. - : Informa UK Limited. - 1499-2027 .- 1708-8186. ; 44:12, s. 721-732
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Tidskriftsartikel (refereegranskat)abstract
- Methodology is proposed for perceptual assessment of both subjective sound quality and speech recognition in such way that results can be compared between these two aspects, Validation is performed with a noise suppression system applied to hearing instruments. A method termed Interpolated Paired Comparison Rating (IPCR) was developed for time efficient assessment of subjective impression of different aspects of sound quality for a variety of noise conditions. The method is based on paired comparisons between processed and unprocessed stimuli, and the results are expressed as the difference in signal-to-noise ratio (dB) between these that give equal subjective impression. For tests of speech recognition in noise, validated adaptive test methods can be used that give results in terms of speech-to-noise ratio. The methodology was shown to be sensitive enough to detect significant mean differences between processed and unprocessed speech in noise, both regarding subjective sound quality and speech recognition ability in groups consisting of 30 subjects. An effect on sound quality from the noise suppression equivalent to about 3-4 dB is required to be statistically significant for a single subject. A corresponding effect of 3-6 dB is required for speech recognition (one-sided test). The magnitude of difference that occurred in the present study for sound quality was sufficient to show significant differences for sound quality within individuals, but this was not the case for speech recognition.
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| 3. |
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| 4. |
- Eneman, K., et al.
(författare)
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Evaluation of signal enhancement algorithms for hearing instruments
- 2008
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Konferensbidrag (refereegranskat)abstract
- In the frame of the HearCom1 project five promising signal enhancement algorithms are validated for future use in hearing instrument devices. To assess the algorithm performance solely based on simulation experiments, a number of physical evaluation measures have been proposed that incorporate basic aspects of normal and impaired human hearing. Additionally, each of the algorithms has been implemented on a common real-time hardware/software platform, which facilitates a profound subjective validation of the algorithm performance. Recently, a multicenter study has been set up across five different test centers in Belgium, the Netherlands, Germany and Switzerland to perceptually evaluate the selected signal enhancement approaches with normally hearing and hearing impaired listeners.
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| 5. |
- Eriksson, Mikael, 1976-
(författare)
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Modelling and Experimental Verification of Direct Drive Wave Energy Conversion : Buoy-Generator Dynamics
- 2007
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis is focused on development of models and modelling of a wave energy converter in operation. Through the thesis linear potential wave theory has been used to describe the wave-buoy interaction. The differences lie in the generator models, in the simplest model the generator is a mechanical damper characterized by a damping factor. In the most advanced generator model the magnetic fields is calculated the by a FE-method, which gives detailed description of the electric properties and the effect it has on the buoy dynamics. Moreover, an equivalent circuit description of the generator has been tested. It has the same accuracy as the field based model but with a strongly enhanced CPU time. All models are verified against full scale experiments. The models are intended to be used for design of the next generation wave energy converters. Further, the developed models have also been used to study what effect buoy geometry and generator damping have on the ability to energy absorption. In the spring 2006 a full scale wave energy converter was installed at the west coast of Sweden. It was in operation and collected data during three months. During that period the load resistance was varied in order to study the effect on the energy absorption. These collected data was then used in the verification of the developed models. In the year 2002 a wave energy project started at Uppsala University; this work is a part of that larger project which intendeds to develop a viable wave energy conversion concept.
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| 6. |
- Henter, Gustav Eje, et al.
(författare)
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Kernel Density Estimation-Based Markov Models with Hidden State
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We consider Markov models of stochastic processes where the next-step conditional distribution is defined by a kernel density estimator (KDE), similar to certain time-series bootstrap schemes from the economic forecasting literature. The KDE Markov models (KDE-MMs) we discuss are nonlinear, nonparametric, fully probabilistic representations of stationary processes with strong asymptotic convergence properties. The models generate new data simply by concatenating points from the training data sequences in a context-sensitive manner, with some added noise. We present novel EM-type maximum-likelihood algorithms for data-driven bandwidth selection in KDE-MMs. Additionally, we augment the KDE-MMs with a hidden state, yielding a new model class, KDE-HMMs. The added state-variable enables long-range memory and signal structure representation, complementing the short-range correlations captured by the Markov process. This is compelling for modelling complex real-world processes such as speech and language data. The paper presents guaranteed-ascent EM-update equations for model parameters in the case of Gaussian kernels, as well as relaxed update formulas that greatly accelerate training in practice. Experiments demonstrate increased held-out set probability for KDE-HMMs on several challenging natural and synthetic data series, compared to traditional techniques such as autoregressive models, HMMs, and their combinations.
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| 7. |
- Henter, Gustav Eje
(författare)
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Probabilistic Sequence Models with Speech and Language Applications
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Series data, sequences of measured values, are ubiquitous. Whenever observations are made along a path in space or time, a data sequence results. To comprehend nature and shape it to our will, or to make informed decisions based on what we know, we need methods to make sense of such data. Of particular interest are probabilistic descriptions, which enable us to represent uncertainty and random variation inherent to the world around us.This thesis presents and expands upon some tools for creating probabilistic models of sequences, with an eye towards applications involving speech and language. Modelling speech and language is not only of use for creating listening, reading, talking, and writing machines---for instance allowing human-friendly interfaces to future computational intelligences and smart devices of today---but probabilistic models may also ultimately tell us something about ourselves and the world we occupy.The central theme of the thesis is the creation of new or improved models more appropriate for our intended applications, by weakening limiting and questionable assumptions made by standard modelling techniques. One contribution of this thesis examines causal-state splitting reconstruction (CSSR), an algorithm for learning discrete-valued sequence models whose states are minimal sufficient statistics for prediction. Unlike many traditional techniques, CSSR does not require the number of process states to be specified a priori, but builds a pattern vocabulary from data alone, making it applicable for language acquisition and the identification of stochastic grammars. A paper in the thesis shows that CSSR handles noise and errors expected in natural data poorly, but that the learner can be extended in a simple manner to yield more robust and stable results also in the presence of corruptions.Even when the complexities of language are put aside, challenges remain. The seemingly simple task of accurately describing human speech signals, so that natural synthetic speech can be generated, has proved difficult, as humans are highly attuned to what speech should sound like. Two papers in the thesis therefore study nonparametric techniques suitable for improved acoustic modelling of speech for synthesis applications. Each of the two papers targets a known-incorrect assumption of established methods, based on the hypothesis that nonparametric techniques can better represent and recreate essential characteristics of natural speech.In the first paper of the pair, Gaussian process dynamical models (GPDMs), nonlinear, continuous state-space dynamical models based on Gaussian processes, are shown to better replicate voiced speech, without traditional dynamical features or assumptions that cepstral parameters follow linear autoregressive processes. Additional dimensions of the state-space are able to represent other salient signal aspects such as prosodic variation. The second paper, meanwhile, introduces KDE-HMMs, asymptotically-consistent Markov models for continuous-valued data based on kernel density estimation, that additionally have been extended with a fixed-cardinality discrete hidden state. This construction is shown to provide improved probabilistic descriptions of nonlinear time series, compared to reference models from different paradigms. The hidden state can be used to control process output, making KDE-HMMs compelling as a probabilistic alternative to hybrid speech-synthesis approaches.A final paper of the thesis discusses how models can be improved even when one is restricted to a fundamentally imperfect model class. Minimum entropy rate simplification (MERS), an information-theoretic scheme for postprocessing models for generative applications involving both speech and text, is introduced. MERS reduces the entropy rate of a model while remaining as close as possible to the starting model. This is shown to produce simplified models that concentrate on the most common and characteristic behaviours, and provides a continuum of simplifications between the original model and zero-entropy, completely predictable output. As the tails of fitted distributions may be inflated by noise or empirical variability that a model has failed to capture, MERS's ability to concentrate on high-probability output is also demonstrated to be useful for denoising models trained on disturbed data.
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| 8. |
- Hongmei, Hu, et al.
(författare)
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Sparsity level in a non-negative matrix factorization based speech strategy in cochlear implants
- 2012
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Ingår i: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO). - : IEEE Computer Society. - 9781467310680 ; , s. 2432-2436
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Konferensbidrag (refereegranskat)abstract
- Non-negative matrix factorization (NMF) has increasinglybeen used as a tool in signal processing in the last years, butit has not been used in the cochlear implants (CIs). Toimprove the performance of CIs in noisy environments, anovel sparse strategy is proposed by applying NMF onenvelops of 22 channels. In the new algorithm, the noisyspeech is first transferred to the time-frequency domain viaa 22- channel filter bank and the envelope in each frequencychannel is extracted; secondly, NMF is applied to theenvelope matrix (envelopegram); finally, the sparsitycondition is applied to the coefficient matrix to get moresparse representation. Speech reception threshold (SRT)subjective experiment was performed in combination withfive objective measurements in order to choose the properparameters for the sparse NMF model.
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| 9. |
- Hällgren, Mathias, 1972-
(författare)
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Hearing and cognition in speech comprehension. Methods and applications
- 2005
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Central auditory processing is complex and can not be evaluated by a single method. This thesis focuses on assessment of some aspects of central auditory functions by the use of dichotic speech tests and cognitive tests that tax functions important for speech processing.Paper A deals with the cognitive effects in dichotic speech testing in elderly hearing-impaired subjects. It was found that different listening tasks in the dichotic tests put different demands on cognitive ability, shown by a varying degree of correlation between cognitive functions and dichotic test parameters. Age-related cognitive decline was strongly connected with problems to perceive stimuli presented to the left ear.Paper B presents a new cognitive test battery sensitive for functions important for speech processing and understanding, performed in text, auditory and audiovisual modalities. The test battery was evaluated in four groups, differing in age and hearing status, and has proven to be useful in assessing the relative contribution of different input-modalities and the effect of age, hearingimpairment and visual contribution on functions important for speech processing.In Paper C the test battery developed in Paper B was used to study listening situations with different kinds of background noise. Interfering noise at +10 dB signal-to-noise ratio has significant negative effects on performance in speech processing tasks and on the effort perceived. Hearing-impaired subjects showed poorer results in noise with temporal variations, and elderly subjects were more distracted by noise with temporal variations, especially by noise with meaningful content. In noise, all subjects, particularly those with impaired hearing, were more dependent upon visual cues than in the quiet condition.Hearing aid benefit in speech processing with and without background noise was studied in Paper D. The test battery developed in Paper B was used together with a standard measure of speech recognition. With hearing aids, speech recognition was improved in the background condition without noise and in the background condition of ordinary speech. Significantly less effort was perceived in the cognitive tests when hearing aids were used, although only minor benefits of hearing aid amplification were seen. This underlines the importance of considering perceived effort as a dimension when evaluating hearing aid benefit, in further research as well as in clinical practice.The results from the studies contribute to the knowledge about speech processing but also to the search for more specific evaluation of speech understanding, incorporating both sensory and cognitive factors.
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| 10. |
- Jalil, Taghia, et al.
(författare)
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Variational Inference for Watson Mixture Model
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Ingår i: IEEE Transactions on Pattern Analysis and Machine Intelligence. - 0162-8828 .- 1939-3539.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This paper addresses modelling data using the multivariate Watson distributions. The Watson distribution is one of thesimplest distributions for analyzing axially symmetric data. This distribution has gained some attention in recent years due to itsmodeling capability. However, its Bayesian inference is fairly understudied due to difficulty in handling the normalization factor. Recentdevelopment of Monte-Carlo Markov chain (MCMC) sampling methods can be applied for this purpose. However, these methods canbe prohibitively slow for practical applications. A deterministic alternative is provided by variational methods that convert inferenceproblems into optimization problems. In this paper, we present a variational inference for Watson mixture model. First, the variationalframework is used to side-step the intractability arising from the coupling of latent states and parameters. Second, the variational freeenergy is further lower bounded in order to avoid intractable moment computation. The proposed approach provides a lower bound onthe log marginal likelihood and retains distributional information over all parameters. Moreover, we show that it can regulate its owncomplexity by pruning unnecessary mixture components while avoiding over-fitting. We discuss potential applications of the modelingwith Watson distributions in the problem of blind source separation, and clustering gene expression data sets.
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