You et al., 2019 - Google Patents
Predicting dementia risk using paralinguistic and memory test features with machine learning modelsYou et al., 2019
- Document ID
- 17312305832473729916
- Author
- You Y
- Ahmed B
- Barr P
- Ballard K
- Valenzuela M
- Publication year
- Publication venue
- 2019 IEEE Healthcare Innovations and Point of Care Technologies,(HI-POCT)
External Links
Snippet
Cognitive reserve exposures are a major class of dementia risk predictors, but a biomarker has proven elusive. Here, we show that paralinguistic features extracted from audio recordings of older participants completing the LOGOS episodic memory test can be used to …
- 206010012289 Dementia 0 title abstract description 31
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
- G10L15/06—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
- G10L17/00—Speaker identification or verification
- G10L17/04—Training, enrolment or model building
-
- 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
- G10L15/18—Speech classification or search using natural language modelling
-
- 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
- G10L25/93—Discriminating between voiced and unvoiced parts of speech signals
-
- 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
- G10L25/90—Pitch determination of speech signals
-
- 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
- G10L13/00—Speech synthesis; Text to speech systems
- G10L13/06—Elementary speech units used in speech synthesisers; Concatenation rules
-
- 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
- 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
- G10L25/78—Detection of presence or absence of voice signals
-
- 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
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
-
- 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
- G10L19/00—Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Haider et al. | An assessment of paralinguistic acoustic features for detection of Alzheimer's dementia in spontaneous speech | |
| Cernak et al. | Characterisation of voice quality of Parkinson’s disease using differential phonological posterior features | |
| Golabbakhsh et al. | Automatic identification of hypernasality in normal and cleft lip and palate patients with acoustic analysis of speech | |
| Satt et al. | Evaluation of speech-based protocol for detection of early-stage dementia. | |
| US10478111B2 (en) | Systems for speech-based assessment of a patient's state-of-mind | |
| KR20240135018A (en) | Multi-modal system and method for voice-based mental health assessment using emotional stimuli | |
| Martínez-Sánchez et al. | Can the acoustic analysis of expressive prosody discriminate schizophrenia? | |
| Zhao et al. | Automatic detection of expressed emotion in Parkinson's disease | |
| Orozco-Arroyave et al. | Voiced/unvoiced transitions in speech as a potential bio-marker to detect parkinson's disease. | |
| You et al. | Predicting dementia risk using paralinguistic and memory test features with machine learning models | |
| Nathan et al. | Assessment of chronic pulmonary disease patients using biomarkers from natural speech recorded by mobile devices | |
| Spinu et al. | A comparison of cepstral coefficients and spectral moments in the classification of Romanian fricatives | |
| Ambrosini et al. | Automatic speech analysis to early detect functional cognitive decline in elderly population | |
| ES3051515T3 (en) | Detection of cognitive impairment | |
| Borsky et al. | Modal and nonmodal voice quality classification using acoustic and electroglottographic features | |
| Dahmani et al. | Vocal folds pathologies classification using Naïve Bayes Networks | |
| Khodabakhsh et al. | Natural language features for detection of Alzheimer's disease in conversational speech | |
| Poellabauer et al. | Challenges in concussion detection using vocal acoustic biomarkers | |
| Vásquez-Correa et al. | Automatic detection of Parkinson's disease from continuous speech recorded in non-controlled noise conditions | |
| Bone et al. | Classifying language-related developmental disorders from speech cues: the promise and the potential confounds. | |
| Yu et al. | Enhancing speech recognition for Parkinson’s disease patient using transfer learning technique | |
| Le et al. | Automatic analysis of speech quality for aphasia treatment | |
| Bayerl et al. | Detecting vocal fatigue with neural embeddings | |
| Gong et al. | Towards an Automated Screening Tool for Developmental Speech and Language Impairments. | |
| JP7731102B2 (en) | Articulation abnormality detection method, articulation abnormality detection device, and program |