1. SENTIMENT ANALYSIS VIA SPEECH/VOICE By: NORHASMIZAWATI IBRAHIM - 813750

2. Outline  Introduction – background of study  Problem statement  Significant of study  Research questions/hypothesis  Research objective  Problem tree  Q & A

3. Introduction – background of study  Definition – sentiment analysis (known as opinion mining)  SA part of speech analytics – emphasize on emotional state.  SA use different scaling method for analyzing common word that relate to +ve, -ve and neutral sentiment.  Applied domain area – medication, sociology, psychology, business & government intelligence, politician & security

4. Cont....  Purpose of SA – to define attitude of human being when they speak/write on certain issues and express the reaction on particular issues.  Type of SA – done using text, voice and speech  Benefit – SA on voices can provide a better method/solution for related domain area. i.e. PD in medication domain by analyzing speech abnormalities

5. Problem Statement  PD – disease that effect changes to body movement, shaking and communication problem.  Critical disease - no cure yet  Risky of PD ages - individual at 60 and above  Statistic - estimated 15,000-20,000 patients suffering PD and the number expected to increase.

6. Cont...  Important to find PD biomarker to detect early symptom as well as monitoring the progression and severity  Recently, researchers have done studies about this issue and keep studying.  There is possibilities to detect early symptom of PD using SA - acoustic and classification analysis on speech abnormalities.

7. Cont...  Fact shows valuable finding in analyzing speech data using machine learning to develop acoustic metrics based on vowel pronunciation.  However, the research assumed difference data set maybe affected due to difference language in each country.  On other research, detection was done by acoustic, vocal and prosodic analysis.  Even the result is promising, it cannot be confirm since the system is newly develop and not tested with pathologic yet.

8. Significant of study  To find solution to analyze speech/voice pattern using huge voice database to discover accuracy of voice pattern using computer algorithms.  Enhance the scope of data set to discover all kind of features dominant to get the accuracy  Possibilities to modelling and combination of available approach by adding some complementary info.

9. Cont...  The rationale of the solution is to ensure the accuracy of the voice diagnose result- number of Parkinson’s disease can be reduce and early stage of PD can have appropriate treatment and avoid huge damage  The result of the study will give positive impact of the life of PD patients in the domain of medication.

10. Research questions /hypothesis  This study is proposed based on these questions: How to detect voices of PD at early stages? How to analyze the various voices pattern? What is the impact of the voice sentiment analysis to related domain?

11. Research objectives  main objective of study is to propose sentiment analysis method to dealing with huge voices database record for early stages of PD detection To identified changes to voice and articulation of early stages of PD patients. To identify the most effective method to early detection of PD. To aid and avoid troubling issues as they emerge.

12. Problem tree Problem detect early symptom of PD speech analyses limitation of difference language small data set speech pathology approvalvoice analysis vocal fold paralysis small data set huge voice database refine algorithm new sample

13. References  References (In IEEE or APA style)   [1] The Michael Stern Parkinson’s Research Foundation. About Parkinson Disease [Online]. Available: http://www.parkinsoninfo.org/about-parkinsons-disease/.http://www.parkinsoninfo.org/about-parkinsons-disease/  [2]Malaysia Parkinson’s Disease Association. (2012, Jan 6). Help Parkinson’s club [online]. Available: http://www.mpda.org.my/help_parkinson_club.ph.http://www.mpda.org.my/help_parkinson_club.ph  [3]T. Anthony. (2009, Nov 26).Awareness is Crucial [online]. Available: http://www.mpda.org.my/articles.php?language=&type=pd_information&9ja847hd0a1=133  [4] Drs. W. Like, W. Xionjuan and C. Bo. Parkinson’s disease – China Stem Cells Medical Center (Rehabilition Centre) [Online]. Available:  http://www.chinastemcell.com.cn/treatmentsdetail.asp?trid=49 http://www.chinastemcell.com.cn/treatmentsdetail.asp?trid=49  [5]S. Sapir, L. O. Ramig, J. L. Spielman, C. Fox. Formant Centralization Ratio: A Proposal for a New Acoustic Measure of Dysarthric Speech. Journal of Speech, Language, and Hearing Research, 2009; 53 (1): 114 DOI:10.1044/1092-4388(2009/08-0184).10.1044/1092-4388(2009/08-0184)  [6]Parkinsoninfo.my. Problem of Diagnosis [online]. Available:  http://www.parkinsoninfo.my/about-parkinson/diagnosis/problem-of-diagnosis/ http://www.parkinsoninfo.my/about-parkinson/diagnosis/problem-of-diagnosis/

14. Cont...  [7]Malaysia Healthy living, (2011, May 5). Understanding Parkinson’s Disease. [online]. Available: http://www.healthtoday.net/malaysia/HealthyLiving/2011/05May/UnderstandingParkinsonsDiseas e.aspx http://www.healthtoday.net/malaysia/HealthyLiving/2011/05May/UnderstandingParkinsonsDiseas e.aspx  [8] N. Singh, V. Pillay, and Y. E. Choonara, “Advances in the treatment of Parkinson’s disease,” Progress in Neurobiology, vol. 81, pp. 29–44, 2007.  [9] S. Sapir, L. Ramig, and C. Fox, “Speech and swallowing disorders in Parkinson’s disease,” Curr Opin Otolaryngol Head Neck Surg, vol. 16, no. 3, pp. 205-210, Jun 2008.  [10]S. Sapir, L. O. Ramig, and C. M. Fox, “Intensive voice treatment in Parkinson’s disease: L ee Silverman Voice Treatment,” Expert Rev neurother, vol. 11, no. 6, pp. 81-830, Jun 2011.  [11]S. Sapir, J. L. Spielman, L.O. Ramig, B.H. Story, and C. Fox, “Effects of intensive voice treatment (the Lee Silverman Voice Treatment [LSVT]) on vowel articulation in dysarthric individual with idiopathic Parkinson disease: acoustic and perceptual finding,” J. Speech Lang. Hear. Res., vol. 50, no. 4, pp. 899-912, Aug 2007.

15. Cont...  [12] M. A. Little, P.E. McSharry, E.J. Hunter, J. Spielman, and L. O. Ramig, “Suitability of  dysphonia measurements for telemonitoring of Parkinson’s disease,” Nature Precedings, no. 713, Sep 2008.  [13] J. Rusz, R. Cmejla, H. Rusickova, and E. Rusicka, “Quantitative acoustic measurements  for characterization of speech and voice disorders in early untreated Parkinson’s disease,” J. Acoust. Soc. Am., vol. 19, no. 1, app. 350-367, Jan 2011.  [14] S. Sapir, L.O. Ramig, J. L. Spielman, and C. Fox, “Formant Centralization Ratio (FCR):  A proposal for a new acoustic measure of dysarthric speech,” J Speech lang Hear Res, vol. 53, no. 1, p. 114, Feb 2010.  [15] S. Skodda, W. Visser, and U. Schlegel, “Vowel articulation in Parkinson’s disease,” J  Voice, vol. 25, no. 4, pp. 467-472, Jul 2011