Tiago Falk | Institut national de la recherche scientifique (original) (raw)

Papers by Tiago Falk

Research paper thumbnail of Single-shot real-time compressed ultrahigh-speed imaging enabled by a snapshot-to-video autoencoder

Research paper thumbnail of Long-term spectro-temporal information for improved automatic speech emotion classification

Research paper thumbnail of Spectral features for automatic blind intelligibility estimation of spastic dysarthric speech

Research paper thumbnail of Spectro-temporal features for robust far-field speaker identification

Interspeech 2008

Page 1. Tiago H. Falk and Wai-Yip Chan ... performance is attained by designing speaker models fo... more Page 1. Tiago H. Falk and Wai-Yip Chan ... performance is attained by designing speaker models for sev-eral different room transfer functions. Online, a “room trans-fer function classifier” is used to determine, from the speech signal, which speaker model to use. ...

Research paper thumbnail of An assessment of the improvement potential of time-frequency masking for speech dereverberation

Research paper thumbnail of Performance comparison of intrusive objective speech intelligibility and quality metrics for cochlear implant users

Research paper thumbnail of New Measures of Heart Rate Variability Based on Subband Tachogram Complexity and Spectral Characteristics for Improved Stress and Anxiety Monitoring in Highly Ecological Settings

Frontiers in Signal Processing

Prediction of mental states, such as stress and anxiety, can be important in situations where red... more Prediction of mental states, such as stress and anxiety, can be important in situations where reduced job performance due to increased mental strain can lead to critical situations (e.g., front-line healthcare workers and first responders). While recent advances in biomedical wearable sensor technologies have allowed for collection of multiple physiological signals in everyday environments, numerous challenges emerge from such uncontrolled settings, including increased noise levels and artifacts, confounding effects from other psychological states (e.g., mental fatigue), as well as physical variables (e.g., physical activity). These factors can be particularly detrimental for heart rate variability (HRV) measures which, in controlled settings, have been shown to accurately track stress and anxiety states. In this paper, we propose two new ways of computing HRV proxies which we show are more robust to such artifacts and confounding factors. The proposed features measure spectral and ...

Research paper thumbnail of PASS: A Multimodal Database of Physical Activity and Stress for Mobile Passive Body/ Brain-Computer Interface Research

Frontiers in Neuroscience

With the burgeoning of wearable devices and passive body/brain-computer interfaces (B/BCIs), auto... more With the burgeoning of wearable devices and passive body/brain-computer interfaces (B/BCIs), automated stress monitoring in everyday settings has gained significant attention recently, with applications ranging from serious games to clinical monitoring. With mobile users, however, challenges arise due to other overlapping (and potentially confounding) physiological responses (e.g., due to physical activity) that may mask the effects of stress, as well as movement artifacts that can be introduced in the measured signals. For example, the classical increase in heart rate can no longer be attributed solely to stress and could be caused by the activity itself. This makes the development of mobile passive B/BCIs challenging. In this paper, we introduce PASS, a multimodal database ofPhysicalActivity andStresScollected from 48 participants. Participants performed tasks of varying stress levels at three different activity levels and provided quantitative ratings of their perceived stress an...

Research paper thumbnail of An improved GMM-based voice quality predictor

Research paper thumbnail of A Multi-condition Training Strategy for Countermeasures Against Spoofing Attacks to Speaker Recognizers

Odyssey 2020 The Speaker and Language Recognition Workshop

Research paper thumbnail of Investigating Speech Enhancement and Perceptual Quality for Speech Emotion Recognition

Research paper thumbnail of Alzheimer's Disease Diagnosis and Severity Level Detection Based on Electroencephalography Modulation Spectral “Patch” Features

IEEE Journal of Biomedical and Health Informatics

Research paper thumbnail of Lessons Learned: Recommendations for Implementing A Longitudinal Study Using Wearable and Environmental Sensors in a Healthcare Organization (Preprint)

JMIR mHealth and uHealth

Although traditional methods of data collection in naturalistic settings can shed light on constr... more Although traditional methods of data collection in naturalistic settings can shed light on constructs of interest to researchers, advances in sensor-based technology allow researchers to capture continuous physiological and behavioral data to provide a more comprehensive understanding of the constructs that are examined in a dynamic health care setting. This study gives examples for implementing technology-facilitated approaches and provides the following recommendations for conducting such longitudinal, sensor-based research, with both environmental and wearable sensors in a health care setting: pilot test sensors and software early and often; build trust with key stakeholders and with potential participants who may be wary of sensor-based data collection and concerned about privacy; generate excitement for novel, new technology during recruitment; monitor incoming sensor data to troubleshoot sensor issues; and consider the logistical constraints of sensor-based research. The study...

Research paper thumbnail of Why is Multimedia Quality of Experience Assessment a Challenging Problem?

Research paper thumbnail of Introduction to the Special Issue on Recent Advances in Biomedical Engineering

Journal of Medical and Biological Engineering

Research paper thumbnail of Lessons Learned: Recommendations for Implementing a Longitudinal Research Study Using Sensors in an Organizational Setting (Preprint)

UNSTRUCTURED While traditional methods of data collection in naturalistic settings can shed light... more UNSTRUCTURED While traditional methods of data collection in naturalistic settings can shed light on constructs of interest to researchers, advances in sensor-based technology allow researchers to capture continuous physiological and behavioral data to provide a more comprehensive understanding of the constructs that are examined in a dynamic healthcare setting. This paper gives examples for implementing technology-facilitated approaches and provides the following recommendations for conducting such longitudinal research in a healthcare setting: pilot test early and often; build trust both with key stakeholders and with potential participants; employ multiple, sample-specific recruitment methods; develop various strategies to sustain and enhance participant compliance; and adopt a flexible approach to project management. The paper describes how these recommendations were successfully implemented by providing examples from a large-scale, sensor-based, longitudinal study of hospital e...

Research paper thumbnail of Spectro-Temporal Electrocardiogram Analysis for Noise-Robust Heart Rate and Heart Rate Variability Measurement

IEEE Journal of Translational Engineering in Health and Medicine

Research paper thumbnail of Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment

Disease markers, 2018

Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the ... more Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databas...

Research paper thumbnail of Modeling Speech Level as a Function of Background Noise Level and Talker-to-Listener Distance for Talkers Wearing Hearing Protection Devices

Journal of speech, language, and hearing research : JSLHR, Jan 20, 2017

Studying the variations in speech levels with changing background noise level and talker-to-liste... more Studying the variations in speech levels with changing background noise level and talker-to-listener distance for talkers wearing hearing protection devices (HPDs) can aid in understanding communication in background noise. Speech was recorded using an intra-aural HPD from 12 different talkers at 5 different distances in 3 different noise conditions and 2 quiet conditions. This article proposes models that can predict the difference in speech level as a function of background noise level and talker-to-listener distance for occluded talkers. The proposed model complements the existing model presented by Pelegrín-García, Smits, Brunskog, and Jeong (2011) and expands on it by taking into account the effects of occlusion and background noise level on changes in speech sound level. Three models of the relationship between vocal effort, background noise level, and talker-to-listener distance for talkers wearing HPDs are presented. The model with the best prediction intervals is a talker-d...

Research paper thumbnail of Electroencephalography Amplitude Modulation Analysis for Automated Affective Tagging of Music Video Clips

Frontiers in computational neuroscience, 2017

The quantity of music content is rapidly increasing and automated affective tagging of music vide... more The quantity of music content is rapidly increasing and automated affective tagging of music video clips can enable the development of intelligent retrieval, music recommendation, automatic playlist generators, and music browsing interfaces tuned to the users' current desires, preferences, or affective states. To achieve this goal, the field of affective computing has emerged, in particular the development of so-called affective brain-computer interfaces, which measure the user's affective state directly from measured brain waves using non-invasive tools, such as electroencephalography (EEG). Typically, conventional features extracted from the EEG signal have been used, such as frequency subband powers and/or inter-hemispheric power asymmetry indices. More recently, the coupling between EEG and peripheral physiological signals, such as the galvanic skin response (GSR), have also been proposed. Here, we show the importance of EEG amplitude modulations and propose several new ...

Research paper thumbnail of Single-shot real-time compressed ultrahigh-speed imaging enabled by a snapshot-to-video autoencoder

Research paper thumbnail of Long-term spectro-temporal information for improved automatic speech emotion classification

Research paper thumbnail of Spectral features for automatic blind intelligibility estimation of spastic dysarthric speech

Research paper thumbnail of Spectro-temporal features for robust far-field speaker identification

Interspeech 2008

Page 1. Tiago H. Falk and Wai-Yip Chan ... performance is attained by designing speaker models fo... more Page 1. Tiago H. Falk and Wai-Yip Chan ... performance is attained by designing speaker models for sev-eral different room transfer functions. Online, a “room trans-fer function classifier” is used to determine, from the speech signal, which speaker model to use. ...

Research paper thumbnail of An assessment of the improvement potential of time-frequency masking for speech dereverberation

Research paper thumbnail of Performance comparison of intrusive objective speech intelligibility and quality metrics for cochlear implant users

Research paper thumbnail of New Measures of Heart Rate Variability Based on Subband Tachogram Complexity and Spectral Characteristics for Improved Stress and Anxiety Monitoring in Highly Ecological Settings

Frontiers in Signal Processing

Prediction of mental states, such as stress and anxiety, can be important in situations where red... more Prediction of mental states, such as stress and anxiety, can be important in situations where reduced job performance due to increased mental strain can lead to critical situations (e.g., front-line healthcare workers and first responders). While recent advances in biomedical wearable sensor technologies have allowed for collection of multiple physiological signals in everyday environments, numerous challenges emerge from such uncontrolled settings, including increased noise levels and artifacts, confounding effects from other psychological states (e.g., mental fatigue), as well as physical variables (e.g., physical activity). These factors can be particularly detrimental for heart rate variability (HRV) measures which, in controlled settings, have been shown to accurately track stress and anxiety states. In this paper, we propose two new ways of computing HRV proxies which we show are more robust to such artifacts and confounding factors. The proposed features measure spectral and ...

Research paper thumbnail of PASS: A Multimodal Database of Physical Activity and Stress for Mobile Passive Body/ Brain-Computer Interface Research

Frontiers in Neuroscience

With the burgeoning of wearable devices and passive body/brain-computer interfaces (B/BCIs), auto... more With the burgeoning of wearable devices and passive body/brain-computer interfaces (B/BCIs), automated stress monitoring in everyday settings has gained significant attention recently, with applications ranging from serious games to clinical monitoring. With mobile users, however, challenges arise due to other overlapping (and potentially confounding) physiological responses (e.g., due to physical activity) that may mask the effects of stress, as well as movement artifacts that can be introduced in the measured signals. For example, the classical increase in heart rate can no longer be attributed solely to stress and could be caused by the activity itself. This makes the development of mobile passive B/BCIs challenging. In this paper, we introduce PASS, a multimodal database ofPhysicalActivity andStresScollected from 48 participants. Participants performed tasks of varying stress levels at three different activity levels and provided quantitative ratings of their perceived stress an...

Research paper thumbnail of An improved GMM-based voice quality predictor

Research paper thumbnail of A Multi-condition Training Strategy for Countermeasures Against Spoofing Attacks to Speaker Recognizers

Odyssey 2020 The Speaker and Language Recognition Workshop

Research paper thumbnail of Investigating Speech Enhancement and Perceptual Quality for Speech Emotion Recognition

Research paper thumbnail of Alzheimer's Disease Diagnosis and Severity Level Detection Based on Electroencephalography Modulation Spectral “Patch” Features

IEEE Journal of Biomedical and Health Informatics

Research paper thumbnail of Lessons Learned: Recommendations for Implementing A Longitudinal Study Using Wearable and Environmental Sensors in a Healthcare Organization (Preprint)

JMIR mHealth and uHealth

Although traditional methods of data collection in naturalistic settings can shed light on constr... more Although traditional methods of data collection in naturalistic settings can shed light on constructs of interest to researchers, advances in sensor-based technology allow researchers to capture continuous physiological and behavioral data to provide a more comprehensive understanding of the constructs that are examined in a dynamic health care setting. This study gives examples for implementing technology-facilitated approaches and provides the following recommendations for conducting such longitudinal, sensor-based research, with both environmental and wearable sensors in a health care setting: pilot test sensors and software early and often; build trust with key stakeholders and with potential participants who may be wary of sensor-based data collection and concerned about privacy; generate excitement for novel, new technology during recruitment; monitor incoming sensor data to troubleshoot sensor issues; and consider the logistical constraints of sensor-based research. The study...

Research paper thumbnail of Why is Multimedia Quality of Experience Assessment a Challenging Problem?

Research paper thumbnail of Introduction to the Special Issue on Recent Advances in Biomedical Engineering

Journal of Medical and Biological Engineering

Research paper thumbnail of Lessons Learned: Recommendations for Implementing a Longitudinal Research Study Using Sensors in an Organizational Setting (Preprint)

UNSTRUCTURED While traditional methods of data collection in naturalistic settings can shed light... more UNSTRUCTURED While traditional methods of data collection in naturalistic settings can shed light on constructs of interest to researchers, advances in sensor-based technology allow researchers to capture continuous physiological and behavioral data to provide a more comprehensive understanding of the constructs that are examined in a dynamic healthcare setting. This paper gives examples for implementing technology-facilitated approaches and provides the following recommendations for conducting such longitudinal research in a healthcare setting: pilot test early and often; build trust both with key stakeholders and with potential participants; employ multiple, sample-specific recruitment methods; develop various strategies to sustain and enhance participant compliance; and adopt a flexible approach to project management. The paper describes how these recommendations were successfully implemented by providing examples from a large-scale, sensor-based, longitudinal study of hospital e...

Research paper thumbnail of Spectro-Temporal Electrocardiogram Analysis for Noise-Robust Heart Rate and Heart Rate Variability Measurement

IEEE Journal of Translational Engineering in Health and Medicine

Research paper thumbnail of Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment

Disease markers, 2018

Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the ... more Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databas...

Research paper thumbnail of Modeling Speech Level as a Function of Background Noise Level and Talker-to-Listener Distance for Talkers Wearing Hearing Protection Devices

Journal of speech, language, and hearing research : JSLHR, Jan 20, 2017

Studying the variations in speech levels with changing background noise level and talker-to-liste... more Studying the variations in speech levels with changing background noise level and talker-to-listener distance for talkers wearing hearing protection devices (HPDs) can aid in understanding communication in background noise. Speech was recorded using an intra-aural HPD from 12 different talkers at 5 different distances in 3 different noise conditions and 2 quiet conditions. This article proposes models that can predict the difference in speech level as a function of background noise level and talker-to-listener distance for occluded talkers. The proposed model complements the existing model presented by Pelegrín-García, Smits, Brunskog, and Jeong (2011) and expands on it by taking into account the effects of occlusion and background noise level on changes in speech sound level. Three models of the relationship between vocal effort, background noise level, and talker-to-listener distance for talkers wearing HPDs are presented. The model with the best prediction intervals is a talker-d...

Research paper thumbnail of Electroencephalography Amplitude Modulation Analysis for Automated Affective Tagging of Music Video Clips

Frontiers in computational neuroscience, 2017

The quantity of music content is rapidly increasing and automated affective tagging of music vide... more The quantity of music content is rapidly increasing and automated affective tagging of music video clips can enable the development of intelligent retrieval, music recommendation, automatic playlist generators, and music browsing interfaces tuned to the users' current desires, preferences, or affective states. To achieve this goal, the field of affective computing has emerged, in particular the development of so-called affective brain-computer interfaces, which measure the user's affective state directly from measured brain waves using non-invasive tools, such as electroencephalography (EEG). Typically, conventional features extracted from the EEG signal have been used, such as frequency subband powers and/or inter-hemispheric power asymmetry indices. More recently, the coupling between EEG and peripheral physiological signals, such as the galvanic skin response (GSR), have also been proposed. Here, we show the importance of EEG amplitude modulations and propose several new ...