Selecting Features for Automatic Screening for Dementia Based on Speech

As the population in developed countries ages, larger numbers of people are at risk of developing dementia. In the near future large-scale time- and cost-efficient screening methods will be needed. Speech can be recorded and analyzed in this manner, and as speech and language are affected early on in the course of dementia, automatic speech processing can provide valuable support for such screening methods.

[1]  Helmut Schmid,et al.  Improvements in Part-of-Speech Tagging with an Application to German , 1999 .

[2]  Brian Roark,et al.  Extraction of Narrative Recall Patterns for Neuropsychological Assessment , 2011, INTERSPEECH.

[3]  Patrick Kenny,et al.  Front-End Factor Analysis for Speaker Verification , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[4]  Swantje Westpfahl,et al.  FOLK-Gold ― A Gold Standard for Part-of-Speech-Tagging of Spoken German , 2016, LREC.

[5]  A. Kertesz,et al.  A study of language functioning in Alzheimer patients , 1982, Brain and Language.

[6]  Eduardo Coutinho,et al.  The INTERSPEECH 2016 Computational Paralinguistics Challenge: Deception, Sincerity & Native Language , 2016, INTERSPEECH.

[7]  Colleen Richey,et al.  Aided diagnosis of dementia type through computer-based analysis of spontaneous speech , 2014, CLPsych@ACL.

[8]  James R. Glass,et al.  Unsupervised Methods for Speaker Diarization: An Integrated and Iterative Approach , 2013, IEEE Transactions on Audio, Speech, and Language Processing.

[9]  M. Martin,et al.  Design und Methodik der Interdisziplinären Längsschnittstudie des Erwachsenenalters , 2000 .

[10]  Gökhan Tür,et al.  Speech-based automated cognitive status assessment , 2010, INTERSPEECH.

[11]  Brian Roark,et al.  Fully Automated Neuropsychological Assessment for Detecting Mild Cognitive Impairment , 2012, INTERSPEECH.

[12]  Tanja Schultz,et al.  Manual and Automatic Transcriptions in Dementia Detection from Speech , 2017, INTERSPEECH.

[13]  J. Toro.  World Alzheimer Report 2013 , 2013 .

[14]  Meysam Asgari,et al.  Predicting mild cognitive impairment from spontaneous spoken utterances , 2017, Alzheimer's & dementia.

[15]  J. Pennebaker,et al.  The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods , 2010 .

[16]  Tanja Schultz,et al.  Speech-Based Detection of Alzheimer's Disease in Conversational German , 2016, INTERSPEECH.

[17]  M. Prince,et al.  World Alzheimer Report 2015 - The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends , 2015 .

[18]  Étienne Brunet,et al.  Le vocabulaire de Jean Giraudoux. Structure et évolution. , 1978 .

[19]  Frank Rudzicz,et al.  Speech Recognition in Alzheimer's Disease and in its Assessment , 2016, INTERSPEECH.

[20]  Gábor Gosztolya,et al.  Automatic detection of mild cognitive impairment from spontaneous speech using ASR , 2015, INTERSPEECH.

[21]  R. Harald Baayen,et al.  How Variable May a Constant be? Measures of Lexical Richness in Perspective , 1998, Comput. Humanit..

[22]  Romola S. Bucks,et al.  Analysis of spontaneous, conversational speech in dementia of Alzheimer type: Evaluation of an objective technique for analysing lexical performance , 2000 .

[23]  James W. Pennebaker,et al.  Linguistic Inquiry and Word Count (LIWC2007) , 2007 .

[24]  Luis A. Hernández Gómez,et al.  A Spoken Language Database for Research on Moderate Cognitive Impairment: Design and Preliminary Analysis , 2014, IberSPEECH.

[25]  J. Pennebaker,et al.  Patterns of Natural Language Use: Disclosure, Personality, and Social Integration , 2001 .

[26]  J. David Schaffer,et al.  Speech Processing Approach for Diagnosing Dementia in an Early Stage , 2017, INTERSPEECH.

[27]  N. Cercone,et al.  Automatic detection and rating of dementia of Alzheimer type through lexical analysis of spontaneous speech , 2005, IEEE International Conference Mechatronics and Automation, 2005.

[28]  Andreas Zenthöfer,et al.  Interdisciplinary longitudinal study on adult development and aging (ILSE) , 2017 .

[29]  Ali Khodabakhsh,et al.  Evaluation of linguistic and prosodic features for detection of Alzheimer’s disease in Turkish conversational speech , 2015, EURASIP J. Audio Speech Music. Process..

[30]  M. Tournier.  Etienne Brunet, Le vocabulaire de J. Giraudoux. Structure et évolution. Statistique et informatique appliquées à l'étude des textes, Genève, éditions Slatkine, 197 , 1981 .

[31]  J. Pennebaker,et al.  Computergestützte quantitative textanalyse: Äquivalenz und robustheit der deutschen Version des Linguistic Inquiry and Word Count. , 2008 .

[32]  Elmar Nöth,et al.  An Analysis of Perplexity to Reveal the Effects of Alzheimer's Disease on Language , 2016, ITG Symposium on Speech Communication.

[33]  Alexandra König,et al.  Speech-based automatic and robust detection of very early dementia , 2014, INTERSPEECH.

[34]  Tanja Schultz,et al.  Towards Automatic Transcription of ILSE ― an Interdisciplinary Longitudinal Study of Adult Development and Aging , 2016, LREC.

[35]  Brian Roark,et al.  Alignment of spoken narratives for automated neuropsychological assessment , 2011, 2011 IEEE Workshop on Automatic Speech Recognition & Understanding.