Vikram C M

Vikram C M
Arizona State University | ASU · Department of Speech and Hearing Science

Doctor of Philosophy

About

30
Publications
3,935
Reads
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151
Citations
Citations since 2017
23 Research Items
145 Citations
2017201820192020202120222023010203040
2017201820192020202120222023010203040
2017201820192020202120222023010203040
2017201820192020202120222023010203040
Introduction
Skills and Expertise

Publications

Publications (30)
Preprint
Full-text available
Spectro-temporal dynamics of consonant-vowel (CV) transition regions are considered to provide robust cues related to articulation. In this work, we propose an objective measure of precise articulation, dubbed the objective articulation measure (OAM), by analyzing the CV transitions segmented around vowel onsets. The OAM is derived based on the pos...
Article
Full-text available
Introduction: Automatic speech processing (ASP) software is a nasality assessment tool. ASP studies focusing on investigating sentences to find nasality and correlating ASP scores with other objective assessment scores measuring nasality are scarce. Hence, the present study aimed at comparing the nasalance values of the ASP software with the nasome...
Article
Spectro-temporal dynamics of consonant-vowel (CV) transition regions are considered to provide robust cues related to articulation. In this work, we propose an objective measure of precise articulation, dubbed the objective articulation measure (OAM), by analyzing the CV transitions segmented around vowel onsets. The OAM is derived based on the pos...
Article
Full-text available
The cleft of the lip and palate (CLP) is a congenital disability affecting the craniofacial region and it impacts the speech production system. The current work focuses on the modification of misarticulations produced for unvoiced stop consonants in CLP speech. Three types of misarticulations are studied: glottal, palatal, and velar stop substituti...
Article
Full-text available
Objectives: Evaluation of hypernasality requires extensive perceptual training by clinicians and extending this training on a large scale internationally is untenable; this compounds the health disparities that already exist among children with cleft. In this work, we present the objective hypernasality measure (OHM), a speech-based algorithm that...
Preprint
Objectives: Evaluation of hypernasality requires extensive perceptual training by clinicians and extending this training on a large scale internationally is untenable; this compounds the health disparities that already exist among children with cleft. In this work, we present the objective hypernasality measure (OHM), a speech analytics algorithm t...
Article
Full-text available
Imprecise articulation is the major issue reported in various types of dysarthria. Detection of articulation errors can help in diagnosis. The cues derived from both the burst and the formant transitions contribute to the discrimination of place of articulation of stops. It is believed that any acoustic deviations in stops due to articulation error...
Article
The presence of velopharyngeal dysfunction, dental occlusion, and mislearned articulation in individuals with cleft lip and palate (CLP) results in the production of misarticulated stop consonants. The present work considers vowel onset points (VOPs) as the anchor points, around which the consonant-vowel (CV) transition regions are segmented to ana...
Article
The presence of velopharyngeal dysfunction in individuals with cleft palate (CP) nasalizes the voiced stops. Due to this, voiced stops (/b/, /d/, /g/) tend to be perceive like nasal consonants (/m/, /n/, /ng/). In this work, a novel algorithm is proposed for the detection of nasalized voiced stops in CP speech using epoch-synchronous features. Spee...
Conference Paper
The individuals with cleft lip and palate (CLP) have a deviant production mechanism of stop consonants due to the presence of velopharyngeal dysfunction and abnormal oral structure. In this work, spectro-temporal analysis of consonant-vowel (CV) transition regions is carried out for the articulation errors produced by children with repaired CLP for...
Article
In this paper, acoustic analysis of misarticulated trills in cleft lip and palate speakers is carried out using excitation source based features: strength of excitation and fundamental frequency, derived from zero-frequency filtered signal, and vocal tract system features: first formant frequency (F1) and trill frequency, derived from the linear pr...
Conference Paper
Full-text available
Vowel space area (VSA) refers to a two-dimensional area, which is bounded by lines joining F 1 and F 2 coordinates of vowels. In the speech of individuals with cleft lip and palate (CLP), the effect of hypernasality introduces the pole-zero pairs in the speech spectrum, which will shift the formants of a target sound. As a result, vowel space in hy...
Article
Epoch extraction from speech involves the suppression of vocal tract resonances, either by linear prediction based inverse filtering or filtering at very low frequency. Degradations due to channel effect and significant attenuation of low frequency components (<300 Hz) create challenges for the epoch extraction from telephone quality speech. An epo...
Article
Full-text available
The present paper proposes wavelet based entropy features and Support Vector Machine (SVM) multi classifier for Heart Rate Variability (HRV) signals classification. The Heart Rate (HR) signals are obtained from ECG signals. The HR signal is decomposed into different frequency bands by wavelet decomposition. The entropy is calculated for each wavele...
Conference Paper
The paper proposes a new method for the phoneme independent normal and pathological voice classification. The new method proposes a wavelet sub band based hybrid classifier built by combining Gaussian Mixture Model-Universal Background Model (GMM-UBM) and Support Vector Machine (SVM). The Mel Frequency Cepstral Coefficients (MFCCs) are computed for...
Conference Paper
This paper proposes a new approach for the phoneme independent pathological voice detection. The phonemes /a/, /i/, /u/ from normal and subjects suffering from voice disorders are recorded. The system uses wavelet based Mel Frequency Cepstral Coefficients (MFCCs) as features, which are given to Gaussian Mixture Model-Universal Background Model (GMM...
Conference Paper
This paper proposes a text independent method for the classification of normal and pathological voices. If the classifier is text dependent i.e classifier is trained for a particular phoneme, then it may difficult for the patient to pronounce the particular phoneme. To overcome this difficulty, a text independent classification method is proposed,...

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