A dataset for voice-based human identity recognition.
Ontology highlight
ABSTRACT:
SUBMITTER: Alsaify BA
PROVIDER: S-EPMC8958529 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
Publications
A dataset for voice-based human identity recognition.
Alsaify Baha' A BA Arja Hadeel S Abu HSA Maayah Baskal Y BY Al-Taweel Masa M MM
Data in brief 20220318
This paper introduces a new English speech dataset suitable for training and evaluating speaker recognition systems. Samples were obtained from non-native English speakers from the Arab region over the course of two months. The dataset was divided into two sub-datasets. Ten samples were collected from each speaker for each sub-dataset. The first sub-dataset contains samples of speakers repeating the phrase "Machine learning 1, 2, 3, 4, 5, 6, 7, 8, 9, 10". The second sub-dataset contains samples ...[more]
Similar Datasets
Project description:Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal lobe is only a facultative component of voice-identity recognition in situations where additional face-identity processing is required.
| S-EPMC5837691 | biostudies-literature
Project description:Listeners exploit small interindividual variations around a generic acoustical structure to discriminate and identify individuals from their voice-a key requirement for social interactions. The human brain contains temporal voice areas (TVA) involved in an acoustic-based representation of voice identity, but the underlying coding mechanisms remain unknown. Indirect evidence suggests that identity representation in these areas could rely on a norm-based coding mechanism. Here, we show by using fMRI that voice identity is coded in the TVA as a function of acoustical distance to two internal voice prototypes (one male, one female)-approximated here by averaging a large number of same-gender voices by using morphing. Voices more distant from their prototype are perceived as more distinctive and elicit greater neuronal activity in voice-sensitive cortex than closer voices-a phenomenon not merely explained by neuronal adaptation. Moreover, explicit manipulations of distance-to-mean by morphing voices toward (or away from) their prototype elicit reduced (or enhanced) neuronal activity. These results indicate that voice-sensitive cortex integrates relevant acoustical features into a complex representation referenced to idealized male and female voice prototypes. More generally, they shed light on remarkable similarities in cerebral representations of facial and vocal identity.
| S-EPMC3690478 | biostudies-literature
Project description:The ability to recognise the identity of others is a key requirement for successful communication. Brain regions that respond selectively to voices exist in humans from early infancy on. Currently, it is unclear whether dysfunction of these voice-sensitive regions can explain voice identity recognition impairments. Here, we used two independent functional magnetic resonance imaging studies to investigate voice processing in a population that has been reported to have no voice-sensitive regions: autism spectrum disorder (ASD). Our results refute the earlier report that individuals with ASD have no responses in voice-sensitive regions: Passive listening to vocal, compared to non-vocal, sounds elicited typical responses in voice-sensitive regions in the high-functioning ASD group and controls. In contrast, the ASD group had a dysfunction in voice-sensitive regions during voice identity but not speech recognition in the right posterior superior temporal sulcus/gyrus (STS/STG)-a region implicated in processing complex spectrotemporal voice features and unfamiliar voices. The right anterior STS/STG correlated with voice identity recognition performance in controls but not in the ASD group. The findings suggest that right STS/STG dysfunction is critical for explaining voice recognition impairments in high-functioning ASD and show that ASD is not characterised by a general lack of voice-sensitive responses.
| S-EPMC5091681 | biostudies-literature
Project description:Recognising the identity of voices is a key ingredient of communication. Visual mechanisms support this ability: recognition is better for voices previously learned with their corresponding face (compared to a control condition). This so-called 'face-benefit' is supported by the fusiform face area (FFA), a region sensitive to facial form and identity. Behavioural findings indicate that the face-benefit increases in noisy listening conditions. The neural mechanisms for this increase are unknown. Here, using functional magnetic resonance imaging, we examined responses in face-sensitive regions while participants recognised the identity of auditory-only speakers (previously learned by face) in high (SNR -4 dB) and low (SNR +4 dB) levels of auditory noise. We observed a face-benefit in both noise levels, for most participants (16 of 21). In high-noise, the recognition of face-learned speakers engaged the right posterior superior temporal sulcus motion-sensitive face area (pSTS-mFA), a region implicated in the processing of dynamic facial cues. The face-benefit in high-noise also correlated positively with increased functional connectivity between this region and voice-sensitive regions in the temporal lobe in the group of 16 participants with a behavioural face-benefit. In low-noise, the face-benefit was robustly associated with increased responses in the FFA and to a lesser extent the right pSTS-mFA. The findings highlight the remarkably adaptive nature of the visual network supporting voice-identity recognition in auditory-only listening conditions.
| S-EPMC8288083 | biostudies-literature
Project description:The ability to recognize people by their voice is an important social behavior. Individuals differ in how they pronounce words, and listeners may take advantage of language-specific knowledge of speech phonology to facilitate recognizing voices. Impaired phonological processing is characteristic of dyslexia and thought to be a basis for difficulty in learning to read. We tested voice-recognition abilities of dyslexic and control listeners for voices speaking listeners' native language or an unfamiliar language. Individuals with dyslexia exhibited impaired voice-recognition abilities compared with controls only for voices speaking their native language. These results demonstrate the importance of linguistic representations for voice recognition. Humans appear to identify voices by making comparisons between talkers' pronunciations of words and listeners' stored abstract representations of the sounds in those words.
| S-EPMC4242590 | biostudies-literature
Project description:This paper presents a dataset for Wi-Fi-based human-to-human interaction recognition that comprises twelve different interactions performed by 40 different pairs of subjects in an indoor environment. Each pair of subjects performed ten trials of each of the twelve interactions and the total number of trials recorded in our dataset for all the 40 pairs of subjects is 4800 trials (i.e., 40 pairs of subjects × 12 interactions × 10 trials). The publicly available CSI tool [1] is used to record the Wi-Fi signals transmitted from a commercial off-the-shelf access point, namely the Sagemcom 2704 access point, to a desktop computer that is equipped with an Intel 5300 network interface card. The recorded Wi-Fi signals consist of the Received Signal Strength Indicator (RSSI) values and the Channel State Information (CSI) values. Unlike the publicly available Wi-Fi-based human activity datasets, which mainly have focused on activities performed by a single human, our dataset provides a collection of Wi-Fi signals that are recorded for 40 different pairs of subjects while performing twelve two-person interactions. The presented dataset can be exploited to advance Wi-Fi-based human activity recognition in different aspects, such as the use of various machine learning algorithms to recognize different human-to-human interactions.
| S-EPMC7240209 | biostudies-literature
Project description:Electroencephalography (EEG)-based open-access datasets are available for emotion recognition studies, where external auditory/visual stimuli are used to artificially evoke pre-defined emotions. In this study, we provide a novel EEG dataset containing the emotional information induced during a realistic human-computer interaction (HCI) using a voice user interface system that mimics natural human-to-human communication. To validate our dataset via neurophysiological investigation and binary emotion classification, we applied a series of signal processing and machine learning methods to the EEG data. The maximum classification accuracy ranged from 43.3% to 90.8% over 38 subjects and classification features could be interpreted neurophysiologically. Our EEG data could be used to develop a reliable HCI system because they were acquired in a natural HCI environment. In addition, auxiliary physiological data measured simultaneously with the EEG data also showed plausible results, i.e., electrocardiogram, photoplethysmogram, galvanic skin response, and facial images, which could be utilized for automatic emotion discrimination independently from, as well as together with the EEG data via the fusion of multi-modal physiological datasets.
| S-EPMC11449991 | biostudies-literature
Project description:Speech carries identity-diagnostic acoustic cues that help individuals recognize each other during vocal-social interactions. In humans, fundamental frequency, formant dispersion and harmonics-to-noise ratio serve as characteristics along which speakers can be reliably separated. The ability to infer a speaker's identity is also adaptive for members of other species (like companion animals) for whom humans (as owners) are relevant. The acoustic bases of speaker recognition in non-humans are unknown. Here, we tested whether dogs can recognize their owner's voice and whether they rely on the same acoustic parameters for such recognition as humans use to discriminate speakers. Stimuli were pre-recorded sentences spoken by the owner and control persons, played through loudspeakers placed behind two non-transparent screens (with each screen hiding a person). We investigated the association between acoustic distance of speakers (examined along several dimensions relevant in intraspecific voice identification) and dogs' behavior. Dogs chose their owner's voice more often than that of control persons', suggesting that they can identify it. Choosing success and time spent looking in the direction of the owner's voice were positively associated, showing that looking time is an index of the ease of choice. Acoustic distance of speakers in mean fundamental frequency and jitter were positively associated with looking time, indicating that the shorter the acoustic distance between speakers with regard to these parameters, the harder the decision. So, dogs use these cues to discriminate their owner's voice from unfamiliar voices. These findings reveal that dogs use some but probably not all acoustic parameters that humans use to identify speakers. Although dogs can detect fine changes in speech, their perceptual system may not be fully attuned to identity-diagnostic cues in the human voice.
| S-EPMC9334438 | biostudies-literature
Project description:Faces and voices are prominent cues for person-identity recognition. Face recognition behavior and associated brain responses can be enhanced by intranasal administration of oxytocin. It is unknown whether oxytocin can also augment voice-identity recognition mechanisms. To find it out is particularly relevant for individuals who have difficulties recognizing voice identity such as individuals diagnosed with autism spectrum disorder (ASD). We conducted a combined behavioral and functional magnetic resonance imaging (fMRI) study to investigate voice-identity recognition following intranasal administration of oxytocin or placebo in a group of adults diagnosed with ASD (full-scale intelligence quotient > 85) and pairwise-matched typically developing (TD) controls. A single dose of 24 IU oxytocin was administered in a randomized, double-blind, placebo-controlled and cross-over design. In the control group, but not in the ASD group, administration of oxytocin compared to placebo increased responses to recognition of voice identity in contrast to speech in the right posterior superior temporal sulcus/gyrus (pSTS/G) - a region implicated in the perceptual analysis of voice-identity information. In the ASD group, the right pSTS/G responses were positively correlated with voice-identity recognition accuracy in the oxytocin condition, but not in the placebo condition. Oxytocin did not improve voice-identity recognition performance at the group level. The ASD compared to the control group had lower right pSTS/G responses to voice-identity recognition. Since ASD is known to have atypical pSTS/G, the results indicate that the potential of intranasal oxytocin to enhance mechanisms for voice-identity recognition might be variable and dependent on the functional integrity of this brain region.
| S-EPMC7341857 | biostudies-literature
Project description:Long-term social recognition is vital for species with complex social networks, where familiar individuals can encounter one another after long periods of separation. For non-human primates who live in dense forest environments, visual access to one another is often limited, and recognition of social partners over distances largely depends on vocal communication. Vocal recognition after years of separation has never been reported in any great ape species, despite their complex societies and advanced social intelligence. Here we show that bonobos, Pan paniscus, demonstrate reliable vocal recognition of social partners, even if they have been separated for five years. We experimentally tested bonobos' responses to the calls of previous group members that had been transferred between captive groups. Despite long separations, subjects responded more intensely to familiar voices than to calls from unknown individuals - the first experimental evidence that bonobos can identify individuals utilising vocalisations even years after their last encounter. Our study also suggests that bonobos may cease to discriminate between familiar and unfamiliar individuals after a period of eight years, indicating that voice representations or interest could be limited in time in this species.
| S-EPMC4766561 | biostudies-literature