1. Instructor:Dr.Veton Kepuska Student:Dileep Narayan.Koneru PRAAT PROSODIC FEATURE EXTRACTION TOOL

2. INTRODUCTION There has been an increasing interest in utilizing a wide variety of knowledge sources in order to perform automatic tagging of speech events, such as sentence boundaries and dialogue acts. In addition to the word spoken, the prosodic content of the speech has been proved quite valuable in a variety of spoken language processing tasks such as sentence segmentation and tagging, dis_uency detection, dialog act segmentation and tagging, and speaker recognition. Here in this project I used an open source prosodic tool for extracting the prosodic analysis.This tool uses praat for its implementation.

3. FEATURES Duration Features F0 Fetures Range Features Movement Features Slope Features Energy Features

4. IMPLEMENTATION Statistical Feature Computation 1. Run Praat 2. Open stats batch.praat from Read\Read from file" on the menu of Praat Objects. 3. Click \Run\Run" on the menu of ScriptEditor.

5. 4. Enter parameters. Type..\demo-wavinfo list.txt and..\demo\work dir in the two boxes, and then check \yes" in the radio box. 5. Click \OK" to start processing with the con_gurations or \Cancel" to close the interface. Clicking the \Apply" button (if available) also starts processing but it keeps the interface on after the work is done. The \Standards" button (if available) gives the option to restore the default con_gurations.

6. 6. Process related information is displayed in the Praat Info Window.After computation is complete, the statistics _les can be found at../demo/work dir/stats files. Prosodic Feature Extraction This is also done in the same way as statistical feature computation. But the main difference is the file main_batch is run instead of stats_batch file

7. The requirements needed for the tool and its basic elements are: Procedures to obtain the basic elements that are directly needed for prosodic feature extraction. The grayed ovals represent operations implemented in the tool, while the grayed rectangles represent the basic elements. Note that Forced Alignment is not a part of the tool, and so it appears in white

8. The use of basic elements for various feature calculations:

9. After the statistic feature calculation we get param files from witch we can view the pitch,raw pitch,stylised pitch,intensity,energy etc From those I presented here the pitch and its informationand the prosodic features table and its information

10. Pitch tier From this we can get the pitch information

11. Pitch information

12. Stylized pitch From this we can get the stylized pitch information

13. Stylized pitch info

14. Prosodic features table

15. Prosodic feature table info

16. RESULT AND COCLUSION Hence the prosodic features of the speech file demo_c.wav are extracted given its word and phone alignment. This prosodic model when combined along with a language model can form an event detection system

17. REFERENCES www.google.com An Open Source Prosodic Feature Extraction Tool Zhongqiang Huang, Lei Chen, Mary Harper