Yagnavajjula et al., 2022 - Google Patents

Detection of neurogenic voice disorders using the fisher vector representation of cepstral features

Yagnavajjula et al., 2022

View HTML
Document ID
2452676923845777639
Author
Yagnavajjula M
Alku P
Rao K
Mitra P
Publication year
Publication venue
Journal of Voice

External Links

Snippet

Neurogenic voice disorders (NVDs) are caused by damage or malfunction of the central or peripheral nervous system that controls vocal fold movement. In this paper, we investigate the potential of the Fisher vector (FV) encoding in automatic detection of people with NVDs …
Continue reading at www.sciencedirect.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination
    • G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L17/00—Speaker identification or verification
    • G10L17/26—Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/02—Feature extraction for speech recognition; Selection of recognition unit
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/065—Adaptation
    • G10L15/07—Adaptation to the speaker
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/08—Speech classification or search
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the analysis technique
    • G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the analysis technique using neural networks
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/003—Changing voice quality, e.g. pitch or formants
    • G10L21/007—Changing voice quality, e.g. pitch or formants characterised by the process used
    • G10L21/013—Adapting to target pitch
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation

Similar Documents

Publication Publication Date Title
Karan et al. Parkinson disease prediction using intrinsic mode function based features from speech signal
Huang et al. Exploiting vocal tract coordination using dilated cnns for depression detection in naturalistic environments
Al-Nasheri et al. Investigation of voice pathology detection and classification on different frequency regions using correlation functions
Narendra et al. Dysarthric speech classification from coded telephone speech using glottal features
Kuresan et al. Fusion of WPT and MFCC feature extraction in Parkinson’s disease diagnosis
Jothilakshmi Automatic system to detect the type of voice pathology
Narendra et al. Automatic assessment of intelligibility in speakers with dysarthria from coded telephone speech using glottal features
Kalluri et al. Automatic speaker profiling from short duration speech data
Khojasteh et al. Parkinson's disease diagnosis based on multivariate deep features of speech signal
Benba et al. Voice assessments for detecting patients with Parkinson’s diseases using PCA and NPCA
He et al. Automatic evaluation of hypernasality based on a cleft palate speech database
US20180277146A1 (en) System and method for anhedonia measurement using acoustic and contextual cues
Syed et al. Inter classifier comparison to detect voice pathologies
Warule et al. Time-frequency analysis of speech signal using Chirplet transform for automatic diagnosis of Parkinson’s disease
Karan et al. Stacked auto-encoder based Time-frequency features of Speech signal for Parkinson disease prediction
Sharma et al. Audio texture and age-wise analysis of disordered speech in children having specific language impairment
Benba et al. Voice assessments for detecting patients with neurological diseases using PCA and NPCA
Iyer et al. A machine learning method to process voice samples for identification of Parkinson’s disease
Wang et al. Continuous speech for improved learning pathological voice disorders
Karan et al. Detection of Parkinson disease using variational mode decomposition of speech signal
Fonseca et al. Discrete wavelet transform and support vector machine applied to pathological voice signals identification
Karan et al. An investigation about the relationship between dysarthria level of speech and the neurological state of Parkinson’s patients
Yagnavajjula et al. Detection of neurogenic voice disorders using the fisher vector representation of cepstral features
Dubey et al. Sinusoidal model-based hypernasality detection in cleft palate speech using CVCV sequence
Dubey et al. Detection and assessment of hypernasality in repaired cleft palate speech using vocal tract and residual features