Vowel discrimination in cats: acquisition, effects of stimulus level, and performance in noise

Phonetic acquisition in cortical dynamics, a computational approach

Many computational theories have been developed to improve artificial phonetic classification performance from linguistic auditory streams. However, less attention has been given to psycholinguistic data and neurophysiological features recently found in cortical tissue. We focus on a context in which basic linguistic units–such as phonemes–are extracted and robustly classified by humans and other animals from complex acoustic streams in speech data. We are especially motivated by the fact that 8-month-old human infants can accomplish segmentation of words from fluent audio streams based exclusively on the statistical relationships between neighboring speech sounds without any kind of supervision. In this paper, we introduce a biologically inspired and fully unsupervised neurocomputational approach that incorporates key neurophysiological and anatomical cortical properties, including columnar organization, spontaneous micro-columnar formation, adaptation to contextual activations and Sparse Distributed Representations (SDRs) produced by means of partial N-Methyl-D-aspartic acid (NMDA) depolarization. Its feature abstraction capabilities show promising phonetic invariance and generalization attributes. Our model improves the performance of a Support Vector Machine (SVM) classifier for monosyllabic, disyllabic and trisyllabic word classification tasks in the presence of environmental disturbances such as white noise, reverberation, and pitch and voice variations. Furthermore, our approach emphasizes potential self-organizing cortical principles achieving improvement without any kind of optimization guidance which could minimize hypothetical loss functions by means of–for example–backpropagation. Thus, our computational model outperforms multiresolution spectro-temporal auditory feature representations using only the statistical sequential structure immerse in the phonotactic rules of the input stream.

In what sense are dogs special? Canine cognition in comparative context

The great increase in the study of dog cognition in the current century has yielded insights into canine cognition in a variety of domains. In this review, we seek to place our enhanced understanding of canine cognition into context. We argue that in order to assess dog cognition, we need to regard dogs from three different perspectives: phylogenetically, as carnivoran and specifically a canid; ecologically, as social, cursorial hunters; and anthropogenically, as a domestic animal. A principled understanding of canine cognition should therefore involve comparing dogs' cognition with that of other carnivorans, other social hunters, and other domestic animals. This paper contrasts dog cognition with what is known about cognition in species that fit into these three categories, with a particular emphasis on wolves, cats, spotted hyenas, chimpanzees, dolphins, horses, and pigeons. We cover sensory cognition, physical cognition, spatial cognition, social cognition, and self-awareness. Although the comparisons are incomplete, because of the limited range of studies of some of the other relevant species, we conclude that dog cognition is influenced by the membership of all three of these groups, and taking all three groups into account, dog cognition does not look exceptional.

Changes in Neuronal Representations of Consonants in the Ascending Auditory System and Their Role in Speech Recognition

A fundamental task of the ascending auditory system is to produce representations that facilitate the recognition of complex sounds. This is particularly challenging in the context of acoustic variability, such as that between different talkers producing the same phoneme. These representations are transformed as information is propagated throughout the ascending auditory system from the inner ear to the auditory cortex (AI). Investigating these transformations and their role in speech recognition is key to understanding hearing impairment and the development of future clinical interventions. Here, we obtained neural responses to an extensive set of natural vowel-consonant-vowel phoneme sequences, each produced by multiple talkers, in three stages of the auditory processing pathway. Auditory nerve (AN) representations were simulated using a model of the peripheral auditory system and extracellular neuronal activity was recorded in the inferior colliculus (IC) and primary auditory cortex (AI) of anaesthetized guinea pigs. A classifier was developed to examine the efficacy of these representations for recognizing the speech sounds. Individual neurons convey progressively less information from AN to AI. Nonetheless, at the population level, representations are sufficiently rich to facilitate recognition of consonants with a high degree of accuracy at all stages indicating a progression from a dense, redundant representation to a sparse, distributed one. We examined the timescale of the neural code for consonant recognition and found that optimal timescales increase throughout the ascending auditory system from a few milliseconds in the periphery to several tens of milliseconds in the cortex. Despite these longer timescales, we found little evidence to suggest that representations up to the level of AI become increasingly invariant to across-talker differences. Instead, our results support the idea that the role of the subcortical auditory system is one of dimensionality expansion, which could provide a basis for flexible classification of arbitrary speech sounds.

Revisiting vocal perception in non-human animals: a review of vowel discrimination, speaker voice recognition, and speaker normalization

The extent to which human speech perception evolved by taking advantage of predispositions and pre-existing features of vertebrate auditory and cognitive systems remains a central question in the evolution of speech. This paper reviews asymmetries in vowel perception, speaker voice recognition, and speaker normalization in non-human animals - topics that have not been thoroughly discussed in relation to the abilities of non-human animals, but are nonetheless important aspects of vocal perception. Throughout this paper we demonstrate that addressing these issues in non-human animals is relevant and worthwhile because many non-human animals must deal with similar issues in their natural environment. That is, they must also discriminate between similar-sounding vocalizations, determine signaler identity from vocalizations, and resolve signaler-dependent variation in vocalizations from conspecifics. Overall, we find that, although plausible, the current evidence is insufficiently strong to conclude that directional asymmetries in vowel perception are specific to humans, or that non-human animals can use voice characteristics to recognize human individuals. However, we do find some indication that non-human animals can normalize speaker differences. Accordingly, we identify avenues for future research that would greatly improve and advance our understanding of these topics.

On the phonetic and syntactic processing abilities of birds: from songs to speech and artificial grammars

Like speech and language, the songs of many songbirds consist of learned, rapidly produced, structured sequences of distinct vocal units, originating from an interplay between experience and learning biases. Songs are species specific, but also show considerable within species variation in elements or element sequencing. This variation implies that birds possess mechanisms to identify, categorize and combine sounds. I review the abilities for speech sound perception and categorization, as well as for grammatical rule learning by birds. Speech sound perception in birds is in many ways comparable to human speech perception. Birds can also detect and generalize patterns underlying artificially arranged strings of vocal elements. However, there is a need for more comparative studies to examine the limits of their rule learning abilities and how they relate to those of humans.

Neural and behavioral investigations into timbre perception

Timbre is the attribute that distinguishes sounds of equal pitch, loudness and duration. It contributes to our perception and discrimination of different vowels and consonants in speech, instruments in music and environmental sounds. Here we begin by reviewing human timbre perception and the spectral and temporal acoustic features that give rise to timbre in speech, musical and environmental sounds. We also consider the perception of timbre by animals, both in the case of human vowels and non-human vocalizations. We then explore the neural representation of timbre, first within the peripheral auditory system and later at the level of the auditory cortex. We examine the neural networks that are implicated in timbre perception and the computations that may be performed in auditory cortex to enable listeners to extract information about timbre. We consider whether single neurons in auditory cortex are capable of representing spectral timbre independently of changes in other perceptual attributes and the mechanisms that may shape neural sensitivity to timbre. Finally, we conclude by outlining some of the questions that remain about the role of neural mechanisms in behavior and consider some potentially fruitful avenues for future research.

Spectral timbre perception in ferrets: discrimination of artificial vowels under different listening conditions

Spectral timbre is an acoustic feature that enables human listeners to determine the identity of a spoken vowel. Despite its importance to sound perception, little is known about the neural representation of sound timbre and few psychophysical studies have investigated timbre discrimination in non-human species. In this study, ferrets were positively conditioned to discriminate artificial vowel sounds in a two-alternative-forced-choice paradigm. Animals quickly learned to discriminate the vowel sound /u/ from /ε/ and were immediately able to generalize across a range of voice pitches. They were further tested in a series of experiments designed to assess how well they could discriminate these vowel sounds under different listening conditions. First, a series of morphed vowels was created by systematically shifting the location of the first and second formant frequencies. Second, the ferrets were tested with single formant stimuli designed to assess which spectral cues they could be using to make their decisions. Finally, vowel discrimination thresholds were derived in the presence of noise maskers presented from either the same or a different spatial location. These data indicate that ferrets show robust vowel discrimination behavior across a range of listening conditions and that this ability shares many similarities with human listeners.

Zebra finches and Dutch adults exhibit the same cue weighting bias in vowel perception

Vocal tract resonances, called formants, are the most important parameters in human speech production and perception. They encode linguistic meaning and have been shown to be perceived by a wide range of species. Songbirds are also sensitive to different formant patterns in human speech. They can categorize words differing only in their vowels based on the formant patterns independent of speaker identity in a way comparable to humans. These results indicate that speech perception mechanisms are more similar between songbirds and humans than realized before. One of the major questions regarding formant perception concerns the weighting of different formants in the speech signal (“acoustic cue weighting”) and whether this process is unique to humans. Using an operant Go/NoGo design, we trained zebra finches to discriminate syllables, whose vowels differed in their first three formants. When subsequently tested with novel vowels, similar in either their first formant or their second and third formants to the familiar vowels, similarity in the higher formants was weighted much more strongly than similarity in the lower formant. Thus, zebra finches indeed exhibit a cue weighting bias. Interestingly, we also found that Dutch speakers when tested with the same paradigm exhibit the same cue weighting bias. This, together with earlier findings, supports the hypothesis that human speech evolution might have exploited general properties of the vertebrate auditory system.

Zebra finches exhibit speaker-independent phonetic perception of human speech

Humans readily distinguish spoken words that closely resemble each other in acoustic structure, irrespective of audible differences between individual voices or sex of the speakers. There is an ongoing debate about whether the ability to form phonetic categories that underlie such distinctions indicates the presence of uniquely evolved, speech-linked perceptual abilities, or is based on more general ones shared with other species. We demonstrate that zebra finches (Taeniopygia guttata) can discriminate and categorize monosyllabic words that differ in their vowel and transfer this categorization to the same words spoken by novel speakers independent of the sex of the voices. Our analysis indicates that the birds, like humans, use intrinsic and extrinsic speaker normalization to make the categorization. This finding shows that there is no need to invoke special mechanisms, evolved together with language, to explain this feature of speech perception.

Phoneme representation and classification in primary auditory cortex

A controversial issue in neurolinguistics is whether basic neural auditory representations found in many animals can account for human perception of speech. This question was addressed by examining how a population of neurons in the primary auditory cortex (A1) of the naive awake ferret encodes phonemes and whether this representation could account for the human ability to discriminate them. When neural responses were characterized and ordered by spectral tuning and dynamics, perceptually significant features including formant patterns in vowels and place and manner of articulation in consonants, were readily visualized by activity in distinct neural subpopulations. Furthermore, these responses faithfully encoded the similarity between the acoustic features of these phonemes. A simple classifier trained on the neural representation was able to simulate human phoneme confusion when tested with novel exemplars. These results suggest that A1 responses are sufficiently rich to encode and discriminate phoneme classes and that humans and animals may build upon the same general acoustic representations to learn boundaries for categorical and robust sound classification.

Predictions of formant-frequency discrimination in noise based on model auditory-nerve responses

To better understand how the auditory system extracts speech signals in the presence of noise, discrimination thresholds for the second formant frequency were predicted with simulations of auditory-nerve responses. These predictions employed either average-rate information or combined rate and timing information, and either populations of model fibers tuned across a wide range of frequencies or a subset of fibers tuned to a restricted frequency range. In general, combined temporal and rate information for a small population of model fibers tuned near the formant frequency was most successful in replicating the trends reported in behavioral data for formant-frequency discrimination. To explore the nature of the temporal information that contributed to these results, predictions based on model auditory-nerve responses were compared to predictions based on the average rates of a population of cross-frequency coincidence detectors. These comparisons suggested that average response rate (count) of cross-frequency coincidence detectors did not effectively extract important temporal information from the auditory-nerve population response. Thus, the relative timing of action potentials across auditory-nerve fibers tuned to different frequencies was not the aspect of the temporal information that produced the trends in formant-frequency discrimination thresholds.

Macaque thresholds for detecting increases in intensity: effects of formant structure

Macaque monkeys, like humans, are more sensitive to differences in formant frequency than to differences in the frequency of pure tones (see Sinnott et al. (1987) J. Comp. Psychol. 94, 401-415; Pfingst (1993) J. Acoust. Soc. Am. 93, 2124-2129; Prosen et al. (1990) J. Acoust. Soc. Am. 88, 2152-2158; Sinnott et al. (1985) J. Acoust. Soc. Am. 78, 1977-1985; Sinnott and Kreiter (1991) J. Acoust. Soc. Am. 89, 2421-2429; for summary, see May et al. (1996) Aud. Neurosci. 3, 135-162). In the discrimination of formant frequency, it appears that the relevant cue for macaque monkeys is relative level differences of the component frequencies (Sommers et al. (1992) J. Acoust. Soc. Am. 91, 3499-3510). To further explore the result of Sommers et al., we trained macaque monkeys (Macaca fuscata) to report detection of a change in the spectral shape of multi-component harmonic complexes. Spectral shape changes were produced by the addition of intensity increments. When the amplitude spectrum of the comparison stimulus was modeled after the /ae/ vowel sound, thresholds for detecting a change from the comparison stimulus were lowest when intensity increments were added at spectral peaks. These results parallel previous data from human subjects, suggesting that both human and monkey subjects may process vowel spectra through simultaneous comparisons of component levels across the spectrum. When the subjects were asked to detect a change from a comparison stimulus with a flat amplitude spectrum, the subjects showed sensitivity that was relatively comparable to that of human subjects tested in other investigations (e.g. Zera et al. (1993) J. Acoust. Soc. Am. 93, 3431-3441). In additional experiments, neither increasing the dynamic range of the /ae/ spectrum nor dynamically varying the amplitude of the increment during the stimulus presentation reliably affected detection thresholds.

Discriminability of vowel representations in cat auditory-nerve fibers after acoustic trauma

This paper attempts to connect deficits seen in the neural representation of speech with perceptual deficits. Responses of auditory-nerve fibers were studied in cats exposed to acoustic trauma. Four synthetic steady-state vowels were used as test signals; these stimuli are identical, except that the second format (F2) resonator in the synthesizer was set to 1.4, 1.5, 1.7, or 2 kHz, producing four spectra that differ mainly in the vicinity of the F2 frequency. These stimuli were presented to a large population (523) of auditory-nerve fibers in four cats with sloping high-frequency threshold shifts that reached 50-70 dB at 2-4 kHz. In normal animals, May et al. [Auditory Neurosci 3, 135-162 (1996)] showed previously that the discharge rates of fibers with best frequencies near the F2 frequencies provide enough information to allow discrimination of these stimuli at the performance levels shown by cats in behavioral experiments. Here it is shown that, after acoustic trauma, there is essentially no rate information which would allow the vowels with different F2 frequencies to be discriminated. However, information that could allow discrimination remains in the temporal (phase-locked) aspects of the responses.

Vowel representations in the ventral cochlear nucleus of the cat: effects of level, background noise, and behavioral state

Single-unit responses were studied in the ventral cochlear nucleus (VCN) of cats as formant and trough features of the vowel /epsilon/ were shifted in the frequency domain to each unit's best frequency (BF; the frequency of greatest sensitivity). Discharge rates sampled with this spectrum manipulation procedure (SMP) were used to estimate vowel representations provided by populations of VCN neurons. In traditional population measures, a good representation of a vowel's formant structure is based on relatively high discharge rates among units with BFs near high-energy formant features and low rates for units with BFs near low-energy spectral troughs. At most vowel levels and in the presence of background noise, chopper units exhibited formant-to-trough rate differences that were larger than VCN primary-like units and auditory-nerve fibers. By contrast, vowel encoding by primary-like units resembled auditory nerve representations for most stimulus conditions. As is seen in the auditory nerve, primary-like units with low spontaneous rates (SR <18 spikes/s) produced better representations than high SR primary-like units at all but the lowest vowel levels. Awake cats exhibited the same general response properties as anesthetized cats but larger between-subject differences in vowel driven rates. The vowel encoding properties of VCN chopper units support previous interpretations that patterns of auditory nerve convergence on cochlear nucleus neurons compensate for limitations in the dynamic range of peripheral neurons.

Effects of bilateral olivocochlear lesions on vowel formant discrimination in cats

Operant conditioning procedures were used to measure the effects of bilateral olivocochlear lesions on the cat's discrimination thresholds for changes in the second formant frequency (deltaF2) of the vowel /epsilon/. Three cats were tested with the formant discrimination task under quiet conditions and in the presence of continuous broadband noise at signal-to-noise ratios (S/Ns) of 23, 13, and 3 dB. In quiet, vowel levels of 50 and 70 dB produced average deltaF2s of 42 and 47 Hz, respectively, and these thresholds did not change significantly in low levels of background noise (S/Ns = 23 and 13 dB). Average deltaF2s increased to 94 and 97 Hz for vowel levels of 50 and 70 dB in the loudest level of background noise (S/N = 3 dB). Average deltaF2 thresholds in quiet and in lower noise levels were only slightly affected when the olivocochlear bundle was lesioned by making bilateral cuts into the floor of the IVth ventricle. In contrast, post-lesion deltaF2 thresholds in the highest noise level were significantly larger than pre-lesion values; the most severely affected subject showed post-lesion discrimination thresholds well over 200 Hz for both 50 and 70 dB vowels. These results suggest that olivocochlear feedback may enhance speech processing in high levels of ambient noise.