Results 301 to 310 of about 10,858,950 (355)
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Acoustic features of vocalization signal in poultry health monitoring
, 2021In precision livestock farming, studies show that bird sound can be employed as a biomarker of health condition. One of the most important steps for this purpose is to study the feasibility of using acoustic features as criteria for disease diagnosis. In
A. Mahdavian +5 more
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Acoustic Features and Neural Representations for Categorical Emotion Recognition from Speech
Interspeech, 2021Many features have been proposed for use in speech emotion recognition, from signal processing features to bag-of-audio-words (BoAW) models to abstract neural representations.
Aaron Keesing +2 more
semanticscholar +1 more source
Journal of the Acoustical Society of America, 2021
This paper presents a simple and easy-to-use method of creating a time-varying signal of the degree of nasalization in vowels, generated from acoustic features measured in oral and nasalized vowel contexts.
Christopher Carignan
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This paper presents a simple and easy-to-use method of creating a time-varying signal of the degree of nasalization in vowels, generated from acoustic features measured in oral and nasalized vowel contexts.
Christopher Carignan
semanticscholar +1 more source
Detecting Alzheimer's Disease Using Interactional and Acoustic Features from Spontaneous Speech
Interspeech, 2021Alzheimer’s Disease (AD) is a form of Dementia that manifests in cognitive decline including memory, language, and changes in behavior. Speech data has proven valuable for inferring cognitive status, used in many health assessment tasks, and can be ...
Shamila Nasreen +2 more
semanticscholar +1 more source
Feature selection for acoustic events detection
Multimedia Tools and Applications, 2013The paper deals with the detection of abnormal situations via captured sound processing. Different settings of feature extraction algorithms were realized and evaluated. Chosen feature sets were used for building the effective parametric representation for gun shots and breaking glass.
Eva Kiktová-Vozarikova +2 more
openaire +1 more source
Screening major depressive disorder using vocal acoustic features in the elderly by sex.
Journal of Affective Disorders, 2021BACKGROUND Vocal acoustic features are potential biomarkers of elderly depression. Previous automated diagnostic tests for depression have employed unstandardized speech samples, and few studies have considered differences in voice reactivity.
Su-Bin Lee +10 more
semanticscholar +1 more source
IEEE International Conference on Acoustics, Speech, and Signal Processing
Speech emotion recognition plays a crucial role in human-computer interaction. However, data distribution of speech signals varies among individuals for emotion recognition.
Zhi-Chen Yuan +3 more
semanticscholar +1 more source
Speech emotion recognition plays a crucial role in human-computer interaction. However, data distribution of speech signals varies among individuals for emotion recognition.
Zhi-Chen Yuan +3 more
semanticscholar +1 more source
Metallic Voice: Physiological and Acoustic Features
Journal of Voice, 2009The metallic voice is usually confused with ring or nasality by singers and nontrained listeners, who are not used to perceptual vocal analysis. They believe a metallic voice results from a rise in fundamental frequency. A diagnostic error in this aspect may lead to lowering pitch, an incorrect procedure that could cause vocal overload and fatigue. The
Eliana Midori, Hanayama +3 more
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Robust features for multilingual acoustic modeling
International Journal of Speech Technology, 2011In this paper, we propose a technique to derive robust features for multilingual acoustic modeling using hidden Markov model---Gaussian mixture models (HMM-GMM). We achieve this by discriminatively combining the phonetic contexts of the target languages (languages in the multilingual system).
C. Santhosh Kumar, V. P. Mohandas
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Acoustic Features for Estimation of Perceptional Similarity
2007This paper describes an examination of acoustic features for the estimation of perceptional similarity between speeches. We firstly extract some acoustic features including personality from speeches of 36 persons. Secondly, we calculate each distance between extracted features using Gaussian Mixture Model (GMM) or Dynamic Time Warping (DTW), and then ...
Yoshihiro Adachi +3 more
openaire +2 more sources

