Simulation of talking faces in the human brain improves auditory speech recognition.
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ABSTRACT:
SUBMITTER: von Kriegstein K
PROVIDER: S-EPMC2365564 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesPeople with Schizophrenia (SZ) show deficits in auditory and audiovisual speech recognition. It is possible that these deficits are related to aberrant early sensory processing, combined with an impaired ability to utilize visual cues to improve speech recognition. In this electroencephalography study we tested this by having SZ and healthy controls (HC) identify different unisensory auditory and bisensory audiovisual syllables at different auditory noise levels.MethodsSZ (N = 24) and HC (N = 21) identified one of three different syllables (/da/, /ga/, /ta/) at three different noise levels (no, low, high). Half the trials were unisensory auditory and the other half provided additional visual input of moving lips. Task-evoked mediofrontal N1 and P2 brain potentials triggered to the onset of the auditory syllables were derived and related to behavioral performance.ResultsIn comparison to HC, SZ showed speech recognition deficits for unisensory and bisensory stimuli. These deficits were primarily found in the no noise condition. Paralleling these observations, reduced N1 amplitudes to unisensory and bisensory stimuli in SZ were found in the no noise condition. In HC the N1 amplitudes were positively related to the speech recognition performance, whereas no such relationships were found in SZ. Moreover, no group differences in multisensory speech recognition benefits and N1 suppression effects for bisensory stimuli were observed.ConclusionOur study suggests that reduced N1 amplitudes reflect early auditory and audiovisual speech processing deficits in SZ. The findings that the amplitude effects were confined to salient speech stimuli and the attenuated relationship with behavioral performance in patients compared to HC, indicates a diminished decoding of the auditory speech signals in SZs. Our study also revealed relatively intact multisensory benefits in SZs, which implies that the observed auditory and audiovisual speech recognition deficits were primarily related to aberrant processing of the auditory syllables.
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Project description:How the human auditory system extracts perceptually relevant acoustic features of speech is unknown. To address this question, we used intracranial recordings from nonprimary auditory cortex in the human superior temporal gyrus to determine what acoustic information in speech sounds can be reconstructed from population neural activity. We found that slow and intermediate temporal fluctuations, such as those corresponding to syllable rate, were accurately reconstructed using a linear model based on the auditory spectrogram. However, reconstruction of fast temporal fluctuations, such as syllable onsets and offsets, required a nonlinear sound representation based on temporal modulation energy. Reconstruction accuracy was highest within the range of spectro-temporal fluctuations that have been found to be critical for speech intelligibility. The decoded speech representations allowed readout and identification of individual words directly from brain activity during single trial sound presentations. These findings reveal neural encoding mechanisms of speech acoustic parameters in higher order human auditory cortex.
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Project description:Previous studies have shown that listeners are better able to understand speech when they are familiar with the talker's voice. In most of these studies, talker familiarity was ensured by explicit voice training; that is, listeners learned to identify the familiar talkers. In the real world, however, the characteristics of familiar talkers are learned incidentally, through communication. The present study investigated whether speech comprehension benefits from implicit voice training; that is, through exposure to talkers' voices without listeners explicitly trying to identify them. During four training sessions, listeners heard short sentences containing a single verb (e.g., "he writes"), spoken by one talker. The sentences were mixed with noise, and listeners identified the verb within each sentence while their speech-reception thresholds (SRT) were measured. In a final test session, listeners performed the same task, but this time they heard different sentences spoken by the familiar talker and three unfamiliar talkers. Familiar and unfamiliar talkers were counterbalanced across listeners. Half of the listeners performed a test session in which the four talkers were presented in separate blocks (blocked paradigm). For the other half, talkers varied randomly from trial to trial (interleaved paradigm). The results showed that listeners had lower SRT when the speech was produced by the familiar talker than the unfamiliar talkers. The type of talker presentation (blocked vs. interleaved) had no effect on this familiarity benefit. These findings suggest that listeners implicitly learn talker-specific information during a speech-comprehension task, and exploit this information to improve the comprehension of novel speech material from familiar talkers.
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Project description:Speech is unique among highly skilled human behaviors in its ease of acquisition by virtually all individuals who have normal hearing and cognitive ability. Vocal imitation is essential for acquiring speech, and it is an important element of social communication. The extent to which age-related changes in cognitive and motor function affect the ability to imitate speech is poorly understood. We analyzed the distributions of response times (RT) for repeating real words and pseudowords during fMRI. The average RT for older and younger participants was not different. In contrast, detailed analysis of RT distributions revealed age-dependent differences that were associated with changes in the time course of the BOLD response and specific patterns of regional activation. RT-dependent activity was observed in the bilateral posterior cingulate, supplementary motor area, and corpus callosum. This approach provides unique insight into the mechanisms associated with changes in speech production with aging.
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Project description:Visual information about speech content from the talker's mouth is often available before auditory information from the talker's voice. Here we examined perceptual and neural responses to words with and without this visual head start. For both types of words, perception was enhanced by viewing the talker's face, but the enhancement was significantly greater for words with a head start. Neural responses were measured from electrodes implanted over auditory association cortex in the posterior superior temporal gyrus (pSTG) of epileptic patients. The presence of visual speech suppressed responses to auditory speech, more so for words with a visual head start. We suggest that the head start inhibits representations of incompatible auditory phonemes, increasing perceptual accuracy and decreasing total neural responses. Together with previous work showing visual cortex modulation (Ozker et al., 2018b) these results from pSTG demonstrate that multisensory interactions are a powerful modulator of activity throughout the speech perception network.
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Project description:The quality of the animal-human relationship and, consequently, the welfare of animals can be improved by gentle interactions such as stroking and talking. The perception of different stimuli during these interactions likely plays a key role in their emotional experience, but studies are scarce. During experiments, the standardization of verbal stimuli could be increased by using a recording. However, the use of a playback might influence the perception differently than "live" talking, which is closer to on-farm practice. Thus, we compared heifers' (n = 28) reactions to stroking while an experimenter was talking soothingly ("live") or while a recording of the experimenter talking soothingly was played ("playback"). Each animal was tested three times per condition and each trial comprised three phases: pre-stimulus, stimulus (stroking and talking) and post-stimulus. In both conditions, similar phrases with positive content were spoken calmly, using long low-pitched vowels. All tests were video recorded and analyzed for behaviors associated with different affective states. Effects on the heifers' cardiac parameters were assessed using analysis of heart rate variability. Independently of the auditory stimuli, longer durations of neck stretching occurred during stroking, supporting our hypothesis of a positive perception of stroking. Observation of ear positions revealed longer durations of the "back up" position and less ear flicking and changes of ear positions during stroking. The predicted decrease in HR during stroking was not confirmed; instead we found a slightly increased mean HR during stroking with a subsequent decrease in HR, which was stronger after stroking with live talking. In combination with differences in HRV parameters, our findings suggest that live talking might have been more pleasurable to the animals and had a stronger relaxing effect than "playback." The results regarding the effects of the degree of standardization of the stimulus on the variability of the data were inconclusive. We thus conclude that the use of recorded auditory stimuli to promote positive affective states during human-animal interactions in experimental settings is possible, but not necessarily preferable.
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Project description:Differences in understanding speech in noise among hearing-impaired individuals cannot be explained entirely by hearing thresholds alone, suggesting the contribution of other factors beyond standard auditory ones as derived from the audiogram. This paper reports two analyses addressing individual differences in the explanation of unaided speech-in-noise performance among n = 438 elderly hearing-impaired listeners (mean = 71.1 ± 5.8 years). The main analysis was designed to identify clinically relevant auditory and non-auditory measures for speech-in-noise prediction using auditory (audiogram, categorical loudness scaling) and cognitive tests (verbal-intelligence test, screening test of dementia), as well as questionnaires assessing various self-reported measures (health status, socio-economic status, and subjective hearing problems). Using stepwise linear regression analysis, 62% of the variance in unaided speech-in-noise performance was explained, with measures Pure-tone average (PTA), Age, and Verbal intelligence emerging as the three most important predictors. In the complementary analysis, those individuals with the same hearing loss profile were separated into hearing aid users (HAU) and non-users (NU), and were then compared regarding potential differences in the test measures and in explaining unaided speech-in-noise recognition. The groupwise comparisons revealed significant differences in auditory measures and self-reported subjective hearing problems, while no differences in the cognitive domain were found. Furthermore, groupwise regression analyses revealed that Verbal intelligence had a predictive value in both groups, whereas Age and PTA only emerged significant in the group of hearing aid NU.
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Project description:Speech segmentation is a crucial step in automatic speech recognition because additional speech analyses are performed for each framed speech segment. Conventional segmentation techniques primarily segment speech using a fixed frame size for computational simplicity. However, this approach is insufficient for capturing the quasi-regular structure of speech, which causes substantial recognition failure in noisy environments. How does the brain handle quasi-regular structured speech and maintain high recognition performance under any circumstance? Recent neurophysiological studies have suggested that the phase of neuronal oscillations in the auditory cortex contributes to accurate speech recognition by guiding speech segmentation into smaller units at different timescales. A phase-locked relationship between neuronal oscillation and the speech envelope has recently been obtained, which suggests that the speech envelope provides a foundation for multi-timescale speech segmental information. In this study, we quantitatively investigated the role of the speech envelope as a potential temporal reference to segment speech using its instantaneous phase information. We evaluated the proposed approach by the achieved information gain and recognition performance in various noisy environments. The results indicate that the proposed segmentation scheme not only extracts more information from speech but also provides greater robustness in a recognition test.
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Project description:Under a "cocktail party" environment, listeners can utilize prior knowledge of the content and voice of the target speech [i.e., auditory speech priming (ASP)] and perceived spatial separation to improve recognition of the target speech among masking speech. Previous studies suggest that these two unmasking cues are not processed independently. However, it is unclear whether the unmasking effects of these two cues are supported by common neural bases. In the current study, we aimed to first confirm that ASP and perceived spatial separation contribute to the improvement of speech recognition interactively in a multitalker condition and further investigate whether there exist intersectant brain substrates underlying both unmasking effects, by introducing these two unmasking cues in a unified paradigm and using functional magnetic resonance imaging. The results showed that neural activations by the unmasking effects of ASP and perceived separation partly overlapped in brain areas: the left pars triangularis (TriIFG) and orbitalis of the inferior frontal gyrus, left inferior parietal lobule, left supramarginal gyrus, and bilateral putamen, all of which are involved in the sensorimotor integration and the speech production. The activations of the left TriIFG were correlated with behavioral improvements caused by ASP and perceived separation. Meanwhile, ASP and perceived separation also enhanced the functional connectivity between the left IFG and brain areas related to the suppression of distractive speech signals: the anterior cingulate cortex and the left middle frontal gyrus, respectively. Therefore, these findings suggest that the motor representation of speech is important for both the unmasking effects of ASP and perceived separation and highlight the critical role of the left IFG in these unmasking effects in "cocktail party" environments.
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Project description:Auditory stimulus reconstruction is a technique that finds the best approximation of the acoustic stimulus from the population of evoked neural activity. Reconstructing speech from the human auditory cortex creates the possibility of a speech neuroprosthetic to establish a direct communication with the brain and has been shown to be possible in both overt and covert conditions. However, the low quality of the reconstructed speech has severely limited the utility of this method for brain-computer interface (BCI) applications. To advance the state-of-the-art in speech neuroprosthesis, we combined the recent advances in deep learning with the latest innovations in speech synthesis technologies to reconstruct closed-set intelligible speech from the human auditory cortex. We investigated the dependence of reconstruction accuracy on linear and nonlinear (deep neural network) regression methods and the acoustic representation that is used as the target of reconstruction, including auditory spectrogram and speech synthesis parameters. In addition, we compared the reconstruction accuracy from low and high neural frequency ranges. Our results show that a deep neural network model that directly estimates the parameters of a speech synthesizer from all neural frequencies achieves the highest subjective and objective scores on a digit recognition task, improving the intelligibility by 65% over the baseline method which used linear regression to reconstruct the auditory spectrogram. These results demonstrate the efficacy of deep learning and speech synthesis algorithms for designing the next generation of speech BCI systems, which not only can restore communications for paralyzed patients but also have the potential to transform human-computer interaction technologies.
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