472 research outputs found

    Visual speech information aids elderly adults in stream segregation

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    Listening to a speaker while hearing another speaker talks is a challenging task for elderly listeners. We show that elderly listeners over the age of 65 with various degrees of age-related hearing loss benefit in this situation from also seeing the speaker they intend to listen to. In a phoneme monitoring task, listeners monitored the speech of a target speaker for either the phoneme /p/ or /k/ while simultaneously hearing a competing speaker. Critically, on some trials, the target speaker was also visible. Elderly listeners benefited in their response times and accuracy levels from seeing the target speaker when monitoring for the less visible /k/, but more so when monitoring for the highly visible /p/. Visual speech therefore aids elderly listeners not only by providing segmental information about the target phoneme, but also by providing more global information that allows for better performance in this adverse listening situation

    Do you see what I mean? The role of visual speech information in lexical representations

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    Human speech is necessarily multimodal and audiovisual redundancies in speech may play a vital role in speech perception across the lifespan. The majority of previous studies have focused particularly on how language is learned from auditory input, but the way in which audiovisual speech information is perceived and comprehended remains less well understood. Here, I examine how audiovisual and visual-only speech information is represented for known words, and if intersensory processing efficiency ability predicts the strength of the lexical representation. To explore the relationship between intersensory processing ability (indexed by matching temporally synchronous auditory and visual stimulation) and the strength of lexical representations, adult subjects participated in an audiovisual word recognition task and the Intersensory Processing Efficiency Protocol (IPEP). Participants were able to reliably identify a correct referent object across manipulations of modality (audiovisual vs visual-only) and pronunciation (correctly vs mispronounced). Correlational analyses did not reveal any relationship between processing efficiency and visual speech information in lexical representations. However, the results presented here suggest that adults’ lexical representations robustly include visual speech information and that visual speech information is sublexically processed during speech perception

    Using Visual Speech Information in Masking Methods for Audio Speaker Separation

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    This work examines whether visual speech infor- mation can be effective within audio masking-based speaker separation to improve the quality and intelligibility of the target speech. Two visual-only methods of generating an audio mask for speaker separation are first developed. These use a deep neural network to map visual speech features to an audio feature space from which both visually-derived binary masks and visually- derived ratio masks are estimated, before application to the speech mixture. Secondly, an audio ratio masking method forms a baseline approach for speaker separation which is extended to exploit visual speech information to form audio-visual ratio masks. Speech quality and intelligibility tests are carried out on the visual-only, audio-only and audio-visual masking methods of speaker separation at mixing levels from -10dB to +10dB. These reveal substantial improvements in the target speech when applying the visual-only and audio-only masks, but with highest performance occurring when combining audio and visual information to create the audio-visual masks

    Using audio and visual information for single channel speaker separation

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    This work proposes a method to exploit both audio and vi- sual speech information to extract a target speaker from a mix- ture of competing speakers. The work begins by taking an ef- fective audio-only method of speaker separation, namely the soft mask method, and modifying its operation to allow visual speech information to improve the separation process. The au- dio input is taken from a single channel and includes the mix- ture of speakers, where as a separate set of visual features are extracted from each speaker. This allows modification of the separation process to include not only the audio speech but also visual speech from each speaker in the mixture. Experimen- tal results are presented that compare the proposed audio-visual speaker separation with audio-only and visual-only methods us- ing both speech quality and speech intelligibility metrics

    Benefit of visual speech information for word comprehension in post-stroke aphasia

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    Aphasia is a language disorder that often involves speech comprehension impairments affecting communication. In face-to-face settings, speech is accompanied by mouth and facial movements, but little is known about the extent to which they benefit aphasic comprehension. This study investigated the benefit of visual information accompanying speech for word comprehension in people with aphasia (PWA) and the neuroanatomic substrates of any benefit. Thirty-six PWA and 13 neurotypical matched control participants performed a picture-word verification task in which they indicated whether a picture of an animate/inanimate object matched a subsequent word produced by an actress in a video. Stimuli were either audiovisual (with visible mouth and facial movements) or auditory-only (still picture of a silhouette) with audio being clear (unedited) or degraded (6-band noise-vocoding). We found that visual speech information was more beneficial for neurotypical participants than PWA, and more beneficial for both groups when speech was degraded. A multivariate lesion-symptom mapping analysis for the degraded speech condition showed that lesions to superior temporal gyrus, underlying insula, primary and secondary somatosensory cortices, and inferior frontal gyrus were associated with reduced benefit of audiovisual compared to auditory-only speech, suggesting that the integrity of these fronto-temporo-parietal regions may facilitate cross-modal mapping. These findings provide initial insights into our understanding of the impact of audiovisual information on comprehension in aphasia and the brain regions mediating any benefit

    Reconstruction of intelligible audio speech from visual speech information

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    The aim of the work conducted in this thesis is to reconstruct audio speech signals using information which can be extracted solely from a visual stream of a speaker's face, with application for surveillance scenarios and silent speech interfaces. Visual speech is limited to that which can be seen of the mouth, lips, teeth, and tongue, where the visual articulators convey considerably less information than in the audio domain, leading to the task being difficult. Accordingly, the emphasis is on the reconstruction of intelligible speech, with less regard given to quality. A speech production model is used to reconstruct audio speech, where methods are presented in this work for generating or estimating the necessary parameters for the model. Three approaches are explored for producing spectral-envelope estimates from visual features as this parameter provides the greatest contribution to speech intelligibility. The first approach uses regression to perform the visual-to-audio mapping, and then two further approaches are explored using vector quantisation techniques and classification models, with long-range temporal information incorporated at the feature and model-level. Excitation information, namely fundamental frequency and aperiodicity, is generated using artificial methods and joint-feature clustering approaches. Evaluations are first performed using mean squared error analyses and objective measures of speech intelligibility to refine the various system configurations, and then subjective listening tests are conducted to determine word-level accuracy, giving real intelligibility scores, of reconstructed speech. The best performing visual-to-audio domain mapping approach, using a clustering-and-classification framework with feature-level temporal encoding, is able to achieve audio-only intelligibility scores of 77 %, and audiovisual intelligibility scores of 84 %, on the GRID dataset. Furthermore, the methods are applied to a larger and more continuous dataset, with less favourable results, but with the belief that extensions to the work presented will yield a further increase in intelligibility

    Investigating the Neural Basis of Audiovisual Speech Perception with Intracranial Recordings in Humans

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    Speech is inherently multisensory, containing auditory information from the voice and visual information from the mouth movements of the talker. Hearing the voice is usually sufficient to understand speech, however in noisy environments or when audition is impaired due to aging or disabilities, seeing mouth movements greatly improves speech perception. Although behavioral studies have well established this perceptual benefit, it is still not clear how the brain processes visual information from mouth movements to improve speech perception. To clarify this issue, I studied the neural activity recorded from the brain surfaces of human subjects using intracranial electrodes, a technique known as electrocorticography (ECoG). First, I studied responses to noisy speech in the auditory cortex, specifically in the superior temporal gyrus (STG). Previous studies identified the anterior parts of the STG as unisensory, responding only to auditory stimulus. On the other hand, posterior parts of the STG are known to be multisensory, responding to both auditory and visual stimuli, which makes it a key region for audiovisual speech perception. I examined how these different parts of the STG respond to clear versus noisy speech. I found that noisy speech decreased the amplitude and increased the across-trial variability of the response in the anterior STG. However, possibly due to its multisensory composition, posterior STG was not as sensitive to auditory noise as the anterior STG and responded similarly to clear and noisy speech. I also found that these two response patterns in the STG were separated by a sharp boundary demarcated by the posterior-most portion of the Heschl’s gyrus. Second, I studied responses to silent speech in the visual cortex. Previous studies demonstrated that visual cortex shows response enhancement when the auditory component of speech is noisy or absent, however it was not clear which regions of the visual cortex specifically show this response enhancement and whether this response enhancement is a result of top-down modulation from a higher region. To test this, I first mapped the receptive fields of different regions in the visual cortex and then measured their responses to visual (silent) and audiovisual speech stimuli. I found that visual regions that have central receptive fields show greater response enhancement to visual speech, possibly because these regions receive more visual information from mouth movements. I found similar response enhancement to visual speech in frontal cortex, specifically in the inferior frontal gyrus, premotor and dorsolateral prefrontal cortices, which have been implicated in speech reading in previous studies. I showed that these frontal regions display strong functional connectivity with visual regions that have central receptive fields during speech perception

    Multisensory Integration Sites Identified by Perception of Spatial Wavelet Filtered Visual Speech Gesture Information

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    Perception of speech is improved when presentation of the audio signal is accompanied by concordant visual speech gesture information. This enhancement is most prevalent when the audio signal is degraded. One potential means by which the brain affords perceptual enhancement is thought to be through the integration of concordant information from multiple sensory channels in a common site of convergence, multisensory integration (MSI) sites. Some studies have identified potential sites in the superior temporal gyrus/sulcus (STG/S) that are responsive to multisensory information from the auditory speech signal and visual speech movement. One limitation of these studies is that they do not control for activity resulting from attentional modulation cued by such things as visual information signaling the onsets and offsets of the acoustic speech signal, as well as activity resulting from MSI of properties of the auditory speech signal with aspects of gross visual motion that are not specific to place of articulation information. This fMRI experiment uses spatial wavelet bandpass filtered Japanese sentences presented with background multispeaker audio noise to discern brain activity reflecting MSI induced by auditory and visual correspondence of place of articulation information that controls for activity resulting from the above-mentioned factors. The experiment consists of a low-frequency (LF) filtered condition containing gross visual motion of the lips, jaw, and head without specific place of articulation information, a midfrequency (MF) filtered condition containing place of articulation information, and an unfiltered (UF) condition. Sites of MSI selectively induced by auditory and visual correspondence of place of articulation information were determined by the presence of activity for both the MF and UF conditions relative to the LF condition. Based on these criteria, sites of MSI were found predominantly in the left middle temporal gyrus (MTG), and the left STG/S (including the auditory cortex). By controlling for additional factors that could also induce greater activity resulting from visual motion information, this study identifies potential MSI sites that we believe are involved with improved speech perception intelligibility

    Reconstructing intelligible audio speech from visual speech features

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    This work describes an investigation into the feasibility of producing intelligible audio speech from only visual speech fea- tures. The proposed method aims to estimate a spectral enve- lope from visual features which is then combined with an arti- ficial excitation signal and used within a model of speech pro- duction to reconstruct an audio signal. Different combinations of audio and visual features are considered, along with both a statistical method of estimation and a deep neural network. The intelligibility of the reconstructed audio speech is measured by human listeners, and then compared to the intelligibility of the video signal only and when combined with the reconstructed audio

    Audio-Visual Automatic Speech Recognition Towards Education for Disabilities

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    Education is a fundamental right that enriches everyone’s life. However, physically challenged people often debar from the general and advanced education system. Audio-Visual Automatic Speech Recognition (AV-ASR) based system is useful to improve the education of physically challenged people by providing hands-free computing. They can communicate to the learning system through AV-ASR. However, it is challenging to trace the lip correctly for visual modality. Thus, this paper addresses the appearance-based visual feature along with the co-occurrence statistical measure for visual speech recognition. Local Binary Pattern-Three Orthogonal Planes (LBP-TOP) and Grey-Level Co-occurrence Matrix (GLCM) is proposed for visual speech information. The experimental results show that the proposed system achieves 76.60 % accuracy for visual speech and 96.00 % accuracy for audio speech recognition
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