The evolution of auditory contrast

This paper reconciles the standpoint that language users do not aim at improving their sound systems with the observation that languages seem to improve their sound systems. Computer simulations of inventories of sibilants show that Optimality-Theoretic learners who optimize their perception grammars automatically introduce a so-called prototype effect, i.e. the phenomenon that the learner’s preferred auditory realization of a certain phonological category is more peripheral than the average auditory realization of this category in her language environment. In production, however, this prototype effect is counteracted by an articulatory effect that limits the auditory form to something that is not too difficult to pronounce. If the prototype effect and the articulatory effect are of a different size, the learner must end up with an auditorily different sound system from that of her language environment. The computer simulations show that, independently of the initial auditory sound system, a stable equilibrium is reached within a small number of generations. In this stable state, the dispersion of the sibilants of the language strikes an optimal balance between articulatory ease and auditory contrast. The important point is that this is derived within a model without any goal-oriented elements such as dispersion constraints

Baseband version of the bat-inspired spectrogram correlation and transformation receiver

Echolocating bats have evolved an excellent ability to detect and discriminate targets in highly challenging environments. They have had more than 50 million years of evolution to optimise their echolocation system with respect to their surrounding environment. Behavioural experiments have shown their exceptional ability to detect and classify targets even in highly cluttered surroundings. The way bats process signals is not exactly the same as in radar and hence it can be useful to investigate the differences. The Spectrogram Correlation And Transformation receiver (SCAT) is an existing model of the bat auditory system that takes into account the physiology and underlying neural organisation in bats which emit chirped signals. In this paper, we propose a baseband receiver equivalent to the SCAT. This will allow biologically inspired signal processing to be applied to radar baseband signals. It will also enable further theoretical analysis of the key concepts, advantages and limitations of the "bat signal processing" for the purpose of target detection, localisation and resolution. The equivalence is demonstrated by comparing the output of the original SCAT to that of our proposed baseband version using both simulated and experimental target echoes. Results show that the baseband receiver provides compatible frequency interference pattern for two closely located scatterers

Energy integration describes sound-intensity coding in an insect auditory system

We investigate the transduction of sound stimuli into neural responses and focus on locust auditory receptor cells. As in other mechanosensory model systems, these neurons integrate acoustic inputs over a fairly broad frequency range. To test three alternative hypotheses about the nature of this spectral integration (amplitude, energy, pressure), we perform intracellular recordings while stimulating with superpositions of pure tones. On the basis of online data analysis and automatic feedback to the stimulus generator, we systematically explore regions in stimulus space that lead to the same level of neural activity. Focusing on such iso-firing-rate regions allows for a rigorous quantitative comparison of the electrophysiological data with predictions from the three hypotheses that is independent of nonlinearities induced by the spike dynamics. We find that the dependence of the firing rates of the receptors on the composition of the frequency spectrum can be well described by an energy-integrator model. This result holds at stimulus onset as well as for the steady-state response, including the case in which adaptation effects depend on the stimulus spectrum. Predictions of the model for the responses to bandpass-filtered noise stimuli are verified accurately. Together, our data suggest that the sound-intensity coding of the receptors can be understood as a three-step process, composed of a linear filter, a summation of the energy contributions in the frequency domain, and a firing-rate encoding of the resulting effective sound intensity. These findings set quantitative constraints for future biophysical models

Spectral and temporal processing in human auditory cortex

Hierarchical processing suggests that spectrally and temporally complex stimuli will evoke more activation than do simple stimuli, particularly in non-primary auditory fields. This hypothesis was tested using two tones, a single frequency tone and a harmonic tone, that were either static or frequency modulated to create four stimuli. We interpret the location of differences in activation by drawing comparisons between fMRI and human cytoarchitectonic data, reported in the same brain space. Harmonic tones produced more activation than single tones in right Heschl's gyrus (HG) and bilaterally in the lateral supratemporal plane (STP). Activation was also greater to frequency-modulated tones than to static tones in these areas, plus in left HG and bilaterally in an anterolateral part of the STP and the superior temporal sulcus. An elevated response magnitude to both frequency-modulated tones was found in the lateral portion of the primary area, and putatively in three surrounding non-primary regions on the lateral STP (one anterior and two posterior to HG). A focal site on the posterolateral STP showed an especially high response to the frequency-modulated harmonic tone. Our data highlight the involvement of both primary and lateral non-primary auditory regions

Frame Theory for Signal Processing in Psychoacoustics

This review chapter aims to strengthen the link between frame theory and signal processing tasks in psychoacoustics. On the one side, the basic concepts of frame theory are presented and some proofs are provided to explain those concepts in some detail. The goal is to reveal to hearing scientists how this mathematical theory could be relevant for their research. In particular, we focus on frame theory in a filter bank approach, which is probably the most relevant view-point for audio signal processing. On the other side, basic psychoacoustic concepts are presented to stimulate mathematicians to apply their knowledge in this field

A Neural Network for Synthesizing the Pitch of an Acoustic Source

This article describes a neural network model capable of generating a spatial representation of the pitch of an acoustic source. Pitch is one of several auditory percepts used by humans to separate multiple sound sources in the environment from each other. The model provides a neural instantiation of a type of "harmonic sieve". It is capable of quantitatively simulating a large body of psychoacoustical data, including new data on octave shift perception.Air Force Office of Scientific Research (90-0128, 90-0175); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI 90-24877); American Society for Engineering Educatio

Learning to Produce Speech with an Altered Vocal Tract: The Role of Auditory Feedback

Modifying the vocal tract alters a speaker’s previously learned acoustic–articulatory relationship. This study investigated the contribution of auditory feedback to the process of adapting to vocal-tract modifications. Subjects said the word /tɑs/ while wearing a dental prosthesis that extended the length of their maxillary incisor teeth. The prosthesis affected /s/ productions and the subjects were asked to learn to produce ‘‘normal’’ /s/’s. They alternately received normal auditory feedback and noise that masked their natural feedback during productions. Acoustic analysis of the speakers’ /s/ productions showed that the distribution of energy across the spectra moved toward that of normal, unperturbed production with increased experience with the prosthesis. However, the acoustic analysis did not show any significant differences in learning dependent on auditory feedback. By contrast, when naive listeners were asked to rate the quality of the speakers’ utterances, productions made when auditory feedback was available were evaluated to be closer to the subjects’ normal productions than when feedback was masked. The perceptual analysis showed that speakers were able to use auditory information to partially compensate for the vocal-tract modification. Furthermore, utterances produced during the masked conditions also improved over a session, demonstrating that the compensatory articulations were learned and available after auditory feedback was removed

Low-frequency oscillatory correlates of auditory predictive processing in cortical-subcortical networks: a MEG-study

Emerging evidence supports the role of neural oscillations as a mechanism for predictive information processing across large-scale networks. However, the oscillatory signatures underlying auditory mismatch detection and information flow between brain regions remain unclear. To address this issue, we examined the contribution of oscillatory activity at theta/alpha-bands (4–8/8–13 Hz) and assessed directed connectivity in magnetoencephalographic data while 17 human participants were presented with sound sequences containing predictable repetitions and order manipulations that elicited prediction-error responses. We characterized the spectro-temporal properties of neural generators using a minimum-norm approach and assessed directed connectivity using Granger Causality analysis. Mismatching sequences elicited increased theta power and phase-locking in auditory, hippocampal and prefrontal cortices, suggesting that theta-band oscillations underlie prediction-error generation in cortical-subcortical networks. Furthermore, enhanced feedforward theta/alpha-band connectivity was observed in auditory-prefrontal networks during mismatching sequences, while increased feedback connectivity in the alpha-band was observed between hippocampus and auditory regions during predictable sounds. Our findings highlight the involvement of hippocampal theta/alpha-band oscillations towards auditory prediction-error generation and suggest a spectral dissociation between inter-areal feedforward vs. feedback signalling, thus providing novel insights into the oscillatory mechanisms underlying auditory predictive processing