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Phonologically-based biomarkers for major depressive disorder

Summary

Of increasing importance in the civilian and military population is the recognition of major depressive disorder at its earliest stages and intervention before the onset of severe symptoms. Toward the goal of more effective monitoring of depression severity, we introduce vocal biomarkers that are derived automatically from phonologically-based measures of speech rate. To assess our measures, we use a 35-speaker free-response speech database of subjects treated for depression over a 6-week duration. We find that dissecting average measures of speech rate into phone-specific characteristics and, in particular, combined phone-duration measures uncovers stronger relationships between speech rate and depression severity than global measures previously reported for a speech-rate biomarker. Results of this study are supported by correlation of our measures with depression severity and classification of depression state with these vocal measures. Our approach provides a general framework for analyzing individual symptom categories through phonological units, and supports the premise that speaking rate can be an indicator of psychomotor retardation severity.
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Summary

Of increasing importance in the civilian and military population is the recognition of major depressive disorder at its earliest stages and intervention before the onset of severe symptoms. Toward the goal of more effective monitoring of depression severity, we introduce vocal biomarkers that are derived automatically from phonologically-based measures of...

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A time-warping framework for speech turbulence-noise component estimation during aperiodic phonation

Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, 22-27 May 2011, pp. 5404-5407.

Summary

The accurate estimation of turbulence noise affects many areas of speech processing including separate modification of the noise component, analysis of degree of speech aspiration for treating pathological voice, the automatic labeling of speech voicing, as well as speaker characterization and recognition. Previous work in the literature has provided methods by which such a high-quality noise component may be estimated in near-periodic speech, but it is known that these methods tend to leak aperiodic phonation (with even slight deviations from periodicity) into the noise-component estimate. In this paper, we improve upon existing algorithms in conditions of aperiodicity by introducing a time-warping based approach to speech noise-component estimation, demonstrating the results on both natural and synthetic speech examples.
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Summary

The accurate estimation of turbulence noise affects many areas of speech processing including separate modification of the noise component, analysis of degree of speech aspiration for treating pathological voice, the automatic labeling of speech voicing, as well as speaker characterization and recognition. Previous work in the literature has provided methods...

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Multi-pitch estimation by a joint 2-D representation of pitch and pitch dynamics

Published in:
INTERSPEECH 2010, 11th Annual Conference of the International Speech Communication Association, 26-30 September 2010, pp. 645-648.

Summary

Multi-pitch estimation of co-channel speech is especially challenging when the underlying pitch tracks are close in pitch value (e.g., when pitch tracks cross). Building on our previous work, we demonstrate the utility of a two-dimensional (2-D) analysis method of speech for this problem by exploiting its joint representation of pitch and pitch-derivative information from distinct speakers. Specifically, we propose a novel multi-pitch estimation method consisting of 1) a data-driven classifier for pitch candidate selection, 2) local pitch and pitch-derivative estimation by k-means clustering, and 3) a Kalman filtering mechanism for pitch tracking and assignment. We evaluate our method on a database of all-voiced speech mixtures and illustrate its capability to estimate pitch tracks in cases where pitch tracks are separate and when they are close in pitch value (e.g., at crossings).
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Summary

Multi-pitch estimation of co-channel speech is especially challenging when the underlying pitch tracks are close in pitch value (e.g., when pitch tracks cross). Building on our previous work, we demonstrate the utility of a two-dimensional (2-D) analysis method of speech for this problem by exploiting its joint representation of pitch...

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Voice production mechanisms following phonosurgical treatment of early glottic cancer

Published in:
Ann. Ontol., Rhinol. Laryngol., Vol. 119, No. 1, 2010, pp. 1-9.

Summary

Although near-normal conversational voices can be achieved with the phonosurgical management of early glottic cancer, there are still acoustic and aerodynamic deficits in vocal function that must be better understood to help further optimize phonosurgical interventions. Stroboscopic assessment is inadequate for this purpose. A newly discovered color high-speed videoendoscopy (HSV) system that included time-synchronized recordings of the acoustic signal was used to perform a detailed examination of voice production mechanisms in 14 subjects. Digital image processing techniques were used to quantify glottal phonatory function and to delineate relationships between vocal fold vibratory properties and acoustic perturbation measures. [not complete]
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Summary

Although near-normal conversational voices can be achieved with the phonosurgical management of early glottic cancer, there are still acoustic and aerodynamic deficits in vocal function that must be better understood to help further optimize phonosurgical interventions. Stroboscopic assessment is inadequate for this purpose. A newly discovered color high-speed videoendoscopy (HSV)...

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Preserving the character of perturbations in scaled pitch contours

Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, 5 March 2010, pp. 417-420.

Summary

The global and fine dynamic components of a pitch contour in voice production, as in the speaking and singing voice, are important for both the meaning and character of an utterance. In speech, for example, slow pitch inflections, rapid pitch accents, and irregular regions all comprise the pitch contour. In applications where all components of a pitch contour are stretched or compressed in the same way, as for example in time-scale modification, an unnatural scaled contour may result. In this paper, we develop a framework for scaling pitch contours, motivated by the goal of maintaining naturalness in time-scale modification of voice. Specifically, we develop a multi-band algorithm to independently modify the slow trajectory and fast perturbation components of a contour for a more natural synthesis, and we present examples where pitch contours representative of speaking and singing voice are lengthened. In the speaking voice, the frequency content of flutter or irregularity is maintained, while slow pitch inflection is simply stretched or compressed. In the singing voice, rapid vibrato is preserved while slower note-to-note variation is scaled as desired.
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Summary

The global and fine dynamic components of a pitch contour in voice production, as in the speaking and singing voice, are important for both the meaning and character of an utterance. In speech, for example, slow pitch inflections, rapid pitch accents, and irregular regions all comprise the pitch contour. In...

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High-pitch formant estimation by exploiting temporal change of pitch

Published in:
Proc. IEEE Trans. on Audio, Speech, and Language Processing, Vol. 18, No. 1, January 2010, pp. 171-186.

Summary

This paper considers the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our work is inspired by auditory perception and physiological studies implicating the use of pitch dynamics in speech by humans. We develop and assess signal processing schemes aimed at exploiting temporal change of pitch to address the high-pitch formant frequency estimation problem. Specifically, we propose a 2-D analysis framework using 2-D transformations of the time-frequency space. In one approach, we project changing spectral harmonics over time to a 1-D function of frequency. In a second approach, we draw upon previous work of Quatieri and Ezzat et al. [1], [2], with similarities to the auditory modeling efforts of Chi et al. [3], where localized 2-D Fourier transforms of the time-frequency space provide improved source-filter separation when pitch is changing. Our methods show quantitative improvements for synthesized vowels with stationary formant structure in comparison to traditional and homomorphic linear prediction. We also demonstrate the feasibility of applying our methods on stationary vowel regions of natural speech spoken by high-pitch females of the TIMIT corpus. Finally, we show improvements afforded by the proposed analysis framework in formant tracking on examples of stationary and time-varying formant structure.
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Summary

This paper considers the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our work is inspired by auditory perception and physiological studies implicating the use of pitch dynamics in speech by humans. We develop and assess signal processing...

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Sinewave parameter estimation using the fast Fan-Chirp Transform

Published in:
Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA, 18-21 October 2009, pp. 349-352.

Summary

Sinewave analysis/synthesis has long been an important tool for audio analysis, modification and synthesis [1]. The recently introduced Fan-Chirp Transform (FChT) [2,3] has been shown to improve the fidelity of sinewave parameter estimates for a harmonic audio signal with rapid frequency modulation [4]. A fast version of the FChT [3] reduces computation but this algorithm presents two factors that affect sinewave parameter estimation. The phase of the fast FChT does not match the phase of the original continuous-time transform and this interferes with the estimation of sinewave phases. Also, the fast FChT requires an interpolation of the input signal and the choice of interpolator affects the speed of the transform and accuracy of the estimated sinewave parameters. In this paper we demonstrate how to modify the phase of the fast FChT such that it can be used to estimate sinewave phases, and we explore the use of various interpolators demonstrating the tradeoff between transform speed and sinewave parameter accuracy.
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Summary

Sinewave analysis/synthesis has long been an important tool for audio analysis, modification and synthesis [1]. The recently introduced Fan-Chirp Transform (FChT) [2,3] has been shown to improve the fidelity of sinewave parameter estimates for a harmonic audio signal with rapid frequency modulation [4]. A fast version of the FChT [3]...

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Towards co-channel speaker separation by 2-D demodulation of spectrograms

Published in:
WASPAA 2009, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 18-21 October 2009, pp. 65-68.

Summary

This paper explores a two-dimensional (2-D) processing approach for co-channel speaker separation of voiced speech. We analyze localized time-frequency regions of a narrowband spectrogram using 2-D Fourier transforms and propose a 2-D amplitude modulation model based on pitch information for single and multi-speaker content in each region. Our model maps harmonically-related speech content to concentrated entities in a transformed 2-D space, thereby motivating 2-D demodulation of the spectrogram for analysis/synthesis and speaker separation. Using a priori pitch estimates of individual speakers, we show through a quantitative evaluation: 1) Utility of the model for representing speech content of a single speaker and 2) Its feasibility for speaker separation. For the separation task, we also illustrate benefits of the model's representation of pitch dynamics relative to a sinusoidal-based separation system.
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Summary

This paper explores a two-dimensional (2-D) processing approach for co-channel speaker separation of voiced speech. We analyze localized time-frequency regions of a narrowband spectrogram using 2-D Fourier transforms and propose a 2-D amplitude modulation model based on pitch information for single and multi-speaker content in each region. Our model maps...

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2-D processing of speech for multi-pitch analysis.

Published in:
INTERSPEECH 2009, 6-10 September 2009.

Summary

This paper introduces a two-dimensional (2-D) processing approach for the analysis of multi-pitch speech sounds. Our framework invokes the short-space 2-D Fourier transform magnitude of a narrowband spectrogram, mapping harmonically related signal components to multiple concentrated entities in a new 2-D space. First, localized time-frequency regions of the spectrogram are analyzed to extract pitch candidates. These candidates are then combined across multiple regions for obtaining separate pitch estimates of each speech-signal component at a single point in time. We refer to this as multi-region analysis (MRA). By explicitly accounting for pitch dynamics within localized time segments, this separability is distinct from that which can be obtained using short-time autocorrelation methods typically employed in state-of-the-art multi-pitch tracking algorithms. We illustrate the feasibility of MRA for multi-pitch estimation on mixtures of synthetic and real speech.
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Summary

This paper introduces a two-dimensional (2-D) processing approach for the analysis of multi-pitch speech sounds. Our framework invokes the short-space 2-D Fourier transform magnitude of a narrowband spectrogram, mapping harmonically related signal components to multiple concentrated entities in a new 2-D space. First, localized time-frequency regions of the spectrogram are...

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Time-varying autoregressive tests for multiscale speech analysis

Published in:
INTERSPEECH 2009, 10th Annual Conf. of the International Speech Communication Association, pp. 2839-2842.

Summary

In this paper we develop hypothesis tests for speech waveform nonstationarity based on time-varying autoregressive models, and demonstrate their efficacy in speech analysis tasks at both segmental and sub-segmental scales. Key to the successful synthesis of these ideas is our employment of a generalized likelihood ratio testing framework tailored to autoregressive coefficient evolutions suitable for speech. After evaluating our framework on speech-like synthetic signals, we present preliminary results for two distinct analysis tasks using speech waveform data. At the segmental level, we develop an adaptive short-time segmentation scheme and evaluate it on whispered speech recordings, while at the sub-segmental level, we address the problem of detecting the glottal flow closed phase. Results show that our hypothesis testing framework can reliably detect changes in the vocal tract parameters across multiple scales, thereby underscoring its broad applicability to speech analysis.
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Summary

In this paper we develop hypothesis tests for speech waveform nonstationarity based on time-varying autoregressive models, and demonstrate their efficacy in speech analysis tasks at both segmental and sub-segmental scales. Key to the successful synthesis of these ideas is our employment of a generalized likelihood ratio testing framework tailored to...

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