Multi-Level Liveness Verification for Face-Voice Biometric Authentication

In this paper we present the details of the multilevel liveness verification (MLLV) framework proposed for realizing a secure face-voice biometric authentication system that can thwart different types of audio and video replay attacks. The proposed MLLV framework based on novel feature extraction and multimodal fusion approaches, uncovers the static and dynamic relationship between voice and face information from speaking faces, and allows multiple levels of security. Experiments with three different speaking corpora VidTIMIT, UCBN and AVOZES shows a significant improvement in system performance in terms of DET curves and equal error rates(EER) for different types of replay and synthesis attacks

Acoustic and Respiratory Characteristics of Infant Vocalization

The purpose of this dissertation was to explore vibratory regime of infant phonation. The first study examined 1) differences in overall levels of acoustic and respiratory variables between different regimes and 2) differences in relationships between the acoustic and respiratory variables among regimes. The second study examined 3) the acoustic and respiratory ranges of modal phonation with respect to other regimes and 4) the range of modal phonation among infants of different ages. Two datasets were used in the study. Dataset I was acquired from eight infants of ages 8-18 months, and Dataset II from one infant of ages 4-6 months. Their vocalizations and respiratory movements were recorded during adult-interaction. Phonated segments were identified through waveform, spectrogram, and auditory inspection, and categorized into six mutually exclusive regimes (modal, pulse, loft, subharmonics, biphonation, and chaos). For each regime segment, the following measurements were made: fundamental frequency (F0), sound pressure level (SPL), expiratory slope, and relative lung volume at regime initiation. A series of linear mixed-effects model analysis and analysis of variance revealed differences in mean F0 between regimes, mean SPL, and mean. Correlations between the acoustic and respiratory variables differed among regimes, indicating their relationships were regime-dependent. The most revealing findings were that regime categories readily distributed into different regions of the intensity-frequency space, and that F0 ranges of modal regime tended to decrease with increasing age. In addition to modal, pulse, and loft distributing around the mid, low, and high intensity-frequency regions, respectively, biphonation and subharmonics were found between modal and loft ranges. The upper end of F0 range for pulse was much higher in infants compared to adults, however, biphonation and subharmonics rarely occurred between pulse and modal ranges. A range of modal F0 was about 500 Hz for the young infant in the vocal expansion stage, and about 200 Hz for older infants in the (post-)canonical stage. Although the results are tentative, this finding suggests that F0 variability decreases with age and phonation becomes more restricted to a lower end of an F0 range

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Evidence of biphonation and source-filter interactions in the bugles of male North American wapiti (Cervus Canadensis)

With an average male body mass of 320 kg, the wapiti, Cervus canadensis, is the largest extant species of Old World deer (Cervinae). Despite this large body size, male wapiti produce whistlelike sexual calls called bugles characterised by an extremely high fundamental frequency. Investigations of the biometry and physiology of the male wapiti’s relatively large larynx have so far failed to account for the production of such a high fundamental frequency. Our examination of spectrograms of male bugles suggested that the complex harmonic structure is best explained by a dual-source model (biphonation), with one source oscillating at a mean of 145 Hz (F0) and the other oscillating independently at an average of 1426 Hz (G0). A combination of anatomical investigations and acoustical modelling indicated that the F0 of male bugles is consistent with the vocal fold dimensions reported in this species, whereas the secondary, much higher source at G0 is more consistent with an aerodynamic whistle produced as air flows rapidly through a narrow supraglottic constriction. We also report a possible interaction between the higher frequency G0 and vocal tract resonances, as G0 transiently locks onto individual formants as the vocal tract is extended. We speculate that male wapiti have evolved such a dualsource phonation to advertise body size at close range (with a relatively low-frequency F0 providing a dense spectrum to highlight size-related information contained in formants) while simultaneously advertising their presence over greater distances using the very highamplitude G0 whistle component

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference

Voice source characterization for prosodic and spectral manipulation

The objective of this dissertation is to study and develop techniques to decompose the speech signal into its two main components: voice source and vocal tract. Our main efforts are on the glottal pulse analysis and characterization. We want to explore the utility of this model in different areas of speech processing: speech synthesis, voice conversion or emotion detection among others. Thus, we will study different techniques for prosodic and spectral manipulation. One of our requirements is that the methods should be robust enough to work with the large databases typical of speech synthesis. We use a speech production model in which the glottal flow produced by the vibrating vocal folds goes through the vocal (and nasal) tract cavities and its radiated by the lips. Removing the effect of the vocal tract from the speech signal to obtain the glottal pulse is known as inverse filtering. We use a parametric model fo the glottal pulse directly in the source-filter decomposition phase. In order to validate the accuracy of the parametrization algorithm, we designed a synthetic corpus using LF glottal parameters reported in the literature, complemented with our own results from the vowel database. The results show that our method gives satisfactory results in a wide range of glottal configurations and at different levels of SNR. Our method using the whitened residual compared favorably to this reference, achieving high quality ratings (Good-Excellent). Our full parametrized system scored lower than the other two ranking in third place, but still higher than the acceptance threshold (Fair-Good). Next we proposed two methods for prosody modification, one for each of the residual representations explained above. The first method used our full parametrization system and frame interpolation to perform the desired changes in pitch and duration. The second method used resampling on the residual waveform and a frame selection technique to generate a new sequence of frames to be synthesized. The results showed that both methods are rated similarly (Fair-Good) and that more work is needed in order to achieve quality levels similar to the reference methods. As part of this dissertation, we have studied the application of our models in three different areas: voice conversion, voice quality analysis and emotion recognition. We have included our speech production model in a reference voice conversion system, to evaluate the impact of our parametrization in this task. The results showed that the evaluators preferred our method over the original one, rating it with a higher score in the MOS scale. To study the voice quality, we recorded a small database consisting of isolated, sustained Spanish vowels in four different phonations (modal, rough, creaky and falsetto) and were later also used in our study of voice quality. Comparing the results with those reported in the literature, we found them to generally agree with previous findings. Some differences existed, but they could be attributed to the difficulties in comparing voice qualities produced by different speakers. At the same time we conducted experiments in the field of voice quality identification, with very good results. We have also evaluated the performance of an automatic emotion classifier based on GMM using glottal measures. For each emotion, we have trained an specific model using different features, comparing our parametrization to a baseline system using spectral and prosodic characteristics. The results of the test were very satisfactory, showing a relative error reduction of more than 20% with respect to the baseline system. The accuracy of the different emotions detection was also high, improving the results of previously reported works using the same database. Overall, we can conclude that the glottal source parameters extracted using our algorithm have a positive impact in the field of automatic emotion classification

Models and Analysis of Vocal Emissions for Biomedical Applications

The Models and Analysis of Vocal Emissions with Biomedical Applications (MAVEBA) workshop came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy