The Experts below are selected from a list of 12651 Experts worldwide ranked by ideXlab platform

Kaustav Bhowmick - One of the best experts on this subject based on the ideXlab platform.

  • A Simple Speech Production System Based on Formant Estimation of a Tongue Articulatory System Using Human Tongue Orientation
    IEEE Access, 2021
    Co-Authors: Palli Padmini, Deepa Gupta, Mohammed Zakariah, Yousef Ajami Alotaibi, Kaustav Bhowmick
    Abstract:

    An algorithm for a potentially non-obtrusive Speech Production System was developed and characterized. The algorithm is primarily based on the articulation of the human tongue referred as tongue articulatory System (TAS) and was cascaded with a previously developed laryngeal model. We developed and optimized statistical formulae for formants of vowels and consonants and studied the model for different ages and genders. The difference between the formant frequencies obtained using both the established vocal tract System and proposed cascaded System was found to be < 5%. The proposed model shows the significance of the articulatory nature of the tongue in human Speech Production. An algorithmic Speech synthesizer was developed, and its output was matched with original Speech signals for English vowels and consonants with an Normalized Root-Mean-Square deviation error (NRMSE) of < 0.15ms. Further, an experimental implementation of the developed algorithm was done, with flex-sensors emulating the tongue in an artificial oral cavity. The experimental test results further confirmed the effectiveness of the algorithm, revealing interesting features under tolerance analyses. This idea relates to a means for compensating for a whole or partial loss of Speech. Such a model can be useful to interpret Speech for tracheostomised patients who have undergone larynx surgery, Speech-disabled due to accidents or voice disorders, medical rehabilitation and for robotics.

  • Sensor based Speech Production System without use of glottis
    2017 International Conference on Advances in Computing Communications and Informatics (ICACCI), 2017
    Co-Authors: Palli Padmini, Shikha Tripathi, Kaustav Bhowmick
    Abstract:

    The present work proposes a Speech Production mechanism using source-filter (Vocal tract) model, with the help of sensors placed in the oral cavity to synthesize Speech. The Speech is produced without involvement of glottis. This is achieved by exciting the articulatory System (Oral cavity) with sensor based input. The proposed System creates a virtual voice for a person who lost his voice due to some disability in vocal tract. The Vocal tract model and articulatory System has been tested with English alphabets (Vowels and consonants) using LabView, which has been validated by perceptual test. The present work mainly focuses on the role of the tongue as Speech articulator.

  • ICACCI - Sensor based Speech Production System without use of glottis
    2017 International Conference on Advances in Computing Communications and Informatics (ICACCI), 2017
    Co-Authors: Palli Padmini, Shikha Tripathi, Kaustav Bhowmick
    Abstract:

    The present work proposes a Speech Production mechanism using source-filter (Vocal tract) model, with the help of sensors placed in the oral cavity to synthesize Speech. The Speech is produced without involvement of glottis. This is achieved by exciting the articulatory System (Oral cavity) with sensor based input. The proposed System creates a virtual voice for a person who lost his voice due to some disability in vocal tract. The Vocal tract model and articulatory System has been tested with English alphabets (Vowels and consonants) using LabView, which has been validated by perceptual test. The present work mainly focuses on the role of the tongue as Speech articulator.

T.j. Gable - One of the best experts on this subject based on the ideXlab platform.

  • Denoising of human Speech using combined acoustic and EM sensor signal processing
    2000 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.00CH37100), 2000
    Co-Authors: L.c. Ng, J F Holzrichter, G.c. Burnett, T.j. Gable
    Abstract:

    Low power EM radar-like sensors have made it possible to measure properties of the human Speech Production System in real-time, without acoustic interference. This greatly enhances the quality and quantify of information for many Speech related applications (see Holzrichter, Burnett, Ng, and Lea, J. Acoustic. Soc. Am. 103 (1) 622 (1998)). By using combined glottal-EM-sensor-and acoustic-signals, segments of voiced, unvoiced, and no-Speech can be reliably defined. Real-time de-noising filters can be constructed to remove noise from the user's corresponding Speech signal.

  • ICASSP - Denoising of human Speech using combined acoustic and EM sensor signal processing
    2000 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.00CH37100), 1
    Co-Authors: G.c. Burnett, J F Holzrichter, T.j. Gable
    Abstract:

    Low power EM radar-like sensors have made it possible to measure properties of the human Speech Production System in real-time, without acoustic interference. This greatly enhances the quality and quantify of information for many Speech related applications (see Holzrichter, Burnett, Ng, and Lea, J. Acoustic. Soc. Am. 103 (1) 622 (1998)). By using combined glottal-EM-sensor-and acoustic-signals, segments of voiced, unvoiced, and no-Speech can be reliably defined. Real-time de-noising filters can be constructed to remove noise from the user's corresponding Speech signal.

John H L Hansen - One of the best experts on this subject based on the ideXlab platform.

  • Fundamentals of Speech Science
    Discrete-Time Processing of Speech Signals, 2009
    Co-Authors: John R. Deller, John H L Hansen, John G. Proakis
    Abstract:

    This chapter contains sections titled: Preamble Speech Communication Anatomy and Physiology of the Speech Production System Phonemics and Phonetics Conclusions Problems

  • Speech Under Stress: Analysis, Modeling and Recognition
    Speaker Classification I, 2007
    Co-Authors: John H L Hansen, Sanjay Patil
    Abstract:

    In this chapter, we consider a range of issues associated with analysis, modeling, and recognition of Speech under stress. We start by defining stress, what could be perceived as stress, and how it affects the Speech Production System. In the discussion that follows, we explore how individuals differ in their perception of stress, and hence understand the cues associated with perceiving stress. Having considered the domains of stress, areas for Speech analysis under stress, we shift to the development of algorithms to estimate, classify or distinguish different stress conditions. We will then conclude with revealing what might be in store for understanding stress, and the development of techniques to overcome the effects of stress for Speech recognition and human-computer interactive Systems.

  • Nonlinear analysis and classification of Speech under stressed conditions
    The Journal of the Acoustical Society of America, 1994
    Co-Authors: Douglas A. Cairns, John H L Hansen
    Abstract:

    The Speech Production System is capable of conveying an abundance of information with regards to sentence text, speaker identity, prosodics, as well as emotion and speaker stress. In an effort to better understand the mechanism of human voice communication, researchers have attempted to determine reliable acoustic indicators of stress using such Speech Production features as fundamental frequency (F0), intensity, spectral tilt, the distribution of spectral energy, and others. Their findings indicate that more work is necessary to propose a general solution. In this study, we hypothesize that Speech consists of a linear and nonlinear component, and that the nonlinear component changes markedly between normal and stressed Speech. To quantify the changes between normal and stressed Speech, a classification procedure was developed based on the nonlinear Teager Energy operator. The Teager Energy operator provides an indirect means of evaluating the nonlinear component of Speech. The System was tested using VC ...

  • Detection of hypernasal Speech using a nonlinear operator
    Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1
    Co-Authors: Douglas A. Cairns, John H L Hansen, J.e. Riski
    Abstract:

    Hypernasal Speech is indicative of an underlying problem in the Speech Production System that results from either a physical defect, or a dysfunctional nervous System. Current clinical methods for determining whether Speech is normal or hypernasal are invasive or awkward. A noninvasive System is proposed to classify Speech as normal or hypernasal based on the nonlinear Teager Energy operator. The performance of the System is evaluated using normal and simulated hypernasal Speech. Results show that the Teager Energy metric reliably detects the presence of hypernasality in a Speech sample. >

  • Speaker Classification (1) - Speech Under Stress: Analysis, Modeling and Recognition
    Lecture Notes in Computer Science, 1
    Co-Authors: John H L Hansen, Sanjay A. Patil
    Abstract:

    In this chapter, we consider a range of issues associated with analysis, modeling, and recognition of Speech under stress. We start by defining stress, what could be perceived as stress, and how it affects the Speech Production System. In the discussion that follows, we explore how individuals differ in their perception of stress, and hence understand the cues associated with perceiving stress. Having considered the domains of stress, areas for Speech analysis under stress, we shift to the development of algorithms to estimate, classify or distinguish different stress conditions. We will then conclude with revealing what might be in store for understanding stress, and the development of techniques to overcome the effects of stress for Speech recognition and human-computer interactive Systems.

Francisco M. De Assis - One of the best experts on this subject based on the ideXlab platform.

  • exploiting nonlinearity of the Speech Production System for voice disorder assessment by recurrence quantification analysis
    Chaos, 2018
    Co-Authors: Vinicius J D Vieira, Silvana Cunha Costa, Suzete L N Correia, Leonardo Wanderley Lopes, Washington C De A Costa, Francisco M. De Assis
    Abstract:

    This work summarizes the research related to digital Speech signal processing with recurrence quantification analysis (RQA) applied to voice disorder assessment. The main motivation for these studies is the fact that RQA is able to exploit the nonlinear dynamical nature of the Speech Production System. Due to the use of recurrence quantification measures to represent the behavior of Speech signals, promising results were obtained in the characterization and classification of laryngeal pathologies and voice disorders. These contributions may help one to evaluate the usability and efficiency of RQA in vocal disorder assessment.This work summarizes the research related to digital Speech signal processing with recurrence quantification analysis (RQA) applied to voice disorder assessment. The main motivation for these studies is the fact that RQA is able to exploit the nonlinear dynamical nature of the Speech Production System. Due to the use of recurrence quantification measures to represent the behavior of Speech signals, promising results were obtained in the characterization and classification of laryngeal pathologies and voice disorders. These contributions may help one to evaluate the usability and efficiency of RQA in vocal disorder assessment.

  • Exploiting nonlinearity of the Speech Production System for voice disorder assessment by recurrence quantification analysis
    Chaos (Woodbury N.Y.), 2018
    Co-Authors: Vinicius J D Vieira, Suzete L N Correia, Leonardo Wanderley Lopes, Washington C De A Costa, Silvana Costa, Francisco M. De Assis
    Abstract:

    This work summarizes the research related to digital Speech signal processing with recurrence quantification analysis (RQA) applied to voice disorder assessment. The main motivation for these studies is the fact that RQA is able to exploit the nonlinear dynamical nature of the Speech Production System. Due to the use of recurrence quantification measures to represent the behavior of Speech signals, promising results were obtained in the characterization and classification of laryngeal pathologies and voice disorders. These contributions may help one to evaluate the usability and efficiency of RQA in vocal disorder assessment.

Palli Padmini - One of the best experts on this subject based on the ideXlab platform.

  • A Simple Speech Production System Based on Formant Estimation of a Tongue Articulatory System Using Human Tongue Orientation
    IEEE Access, 2021
    Co-Authors: Palli Padmini, Deepa Gupta, Mohammed Zakariah, Yousef Ajami Alotaibi, Kaustav Bhowmick
    Abstract:

    An algorithm for a potentially non-obtrusive Speech Production System was developed and characterized. The algorithm is primarily based on the articulation of the human tongue referred as tongue articulatory System (TAS) and was cascaded with a previously developed laryngeal model. We developed and optimized statistical formulae for formants of vowels and consonants and studied the model for different ages and genders. The difference between the formant frequencies obtained using both the established vocal tract System and proposed cascaded System was found to be < 5%. The proposed model shows the significance of the articulatory nature of the tongue in human Speech Production. An algorithmic Speech synthesizer was developed, and its output was matched with original Speech signals for English vowels and consonants with an Normalized Root-Mean-Square deviation error (NRMSE) of < 0.15ms. Further, an experimental implementation of the developed algorithm was done, with flex-sensors emulating the tongue in an artificial oral cavity. The experimental test results further confirmed the effectiveness of the algorithm, revealing interesting features under tolerance analyses. This idea relates to a means for compensating for a whole or partial loss of Speech. Such a model can be useful to interpret Speech for tracheostomised patients who have undergone larynx surgery, Speech-disabled due to accidents or voice disorders, medical rehabilitation and for robotics.

  • Sensor based Speech Production System without use of glottis
    2017 International Conference on Advances in Computing Communications and Informatics (ICACCI), 2017
    Co-Authors: Palli Padmini, Shikha Tripathi, Kaustav Bhowmick
    Abstract:

    The present work proposes a Speech Production mechanism using source-filter (Vocal tract) model, with the help of sensors placed in the oral cavity to synthesize Speech. The Speech is produced without involvement of glottis. This is achieved by exciting the articulatory System (Oral cavity) with sensor based input. The proposed System creates a virtual voice for a person who lost his voice due to some disability in vocal tract. The Vocal tract model and articulatory System has been tested with English alphabets (Vowels and consonants) using LabView, which has been validated by perceptual test. The present work mainly focuses on the role of the tongue as Speech articulator.

  • ICACCI - Sensor based Speech Production System without use of glottis
    2017 International Conference on Advances in Computing Communications and Informatics (ICACCI), 2017
    Co-Authors: Palli Padmini, Shikha Tripathi, Kaustav Bhowmick
    Abstract:

    The present work proposes a Speech Production mechanism using source-filter (Vocal tract) model, with the help of sensors placed in the oral cavity to synthesize Speech. The Speech is produced without involvement of glottis. This is achieved by exciting the articulatory System (Oral cavity) with sensor based input. The proposed System creates a virtual voice for a person who lost his voice due to some disability in vocal tract. The Vocal tract model and articulatory System has been tested with English alphabets (Vowels and consonants) using LabView, which has been validated by perceptual test. The present work mainly focuses on the role of the tongue as Speech articulator.