1. Temple University Goals : 1.Down sample 20 khz TIDigits data to 16 khz. 2. Use Down sample data run regression test and Compare results posted in Sphinx-4 website 3. Based on the results, make decisions (issue with microprocessor, floating point etc.) By Jaykrishna shukla, Mubin Ahmed and Cara Santin

2. Temple University Learned : 1.Cygwin not effective to run Sox 2. effective to run linux command line interface to build application 3.Easy to install

3. Temple University Training Acoustic model using Sphinx Train URL:

4. Temple University Introduction to Training Q1.What is acoustic model ? A1. model used by a speech recognizer for decoding language spoken by a person and modeling numerically how the language sounds when spoken in a form that can be stored on a computer. Q2. what is training A2. process that wants to converge on a solution yielding the most likely sequence of vectors for a given acoustic unit. Q3. why is training required? A3. In order to generate a set of acoustic model for any audio data, one needs to follow a particular set of steps which is named as training, hence to generate acoustic model, training is required.

5. Temple University The Flow chart for the Training Procedure Training acoustic model using SphinxTrain 1.0 overview

6. Temple University SphinxTrain 1.0 & auto generation The new version of sphinx train has a build all option, that generates all the required files that were shown in the flow chart from previous slide. However, in order to do object specific function, one needs to modify the config file according to the purpose of the task.

7. Temple University This week’s accomplishment The two major goals that I achieved this week were: Finished the complete training process for the an4 demo. Worked on generating the feature model for the TI Digit short test data. Sample output of a training process (it took more than 20 min to compile this code)

8. Temple University Generating the feature vectors There two main step in generating the feature vector: 1. Generate the.Fileids file (it is just the path list of all the data file) 2. Modify the Make_feats (perl script) to in order to read the correct data in and change the default settings that the SphinxTrain comes with.

9. Temple University Conclusion and Future The main problem in feature generation is that the Make_feats file has default settings for the an4 tutorial, hence to getting it working we have to change the configuration for both the make_feats file and the SphinxTrain connfig file (because the config file determines what goes in to the make_feats file. Follow the below Example )

10. Temple University Training Acoustic model using Sphinx Train Jaykrishna shukla,Mubin Amehed& cara Santin Department of Electrical and Computer Engineering Temple University URL:

11. Temple University: Slide 10 Introduction to Training Q1.What is acoustic model ? A1. model used by a speech recognizer for decoding language spoken by a person and modeling numerically how the language sounds when spoken in a form that can be stored on a computer. Q2. what is training A2. process that wants to converge on a solution yielding the most likely sequence of vectors for a given acoustic unit. Q3. why is training required? A3. In order to generate a set of acoustic model for any audio data, one needs to follow a particular set of steps which is named as training, hence to generate acoustic model, training is required.

12. Temple University: Slide 11 The Flow chart for the Training Procedure Training acoustic model using SphinxTrain 1.0 overview

13. Temple University: Slide 12 SphinxTrain 1.0 & auto generation The new version of sphinx train has a build all option, that generates all the required files that were shown in the flow chart from previous slide. However, in order to do object specific function, one needs to modify the config file according to the purpose of the task.

14. Temple University: Slide 13 This week’s accomplishment The two major goals that I achieved this week were: Finished the complete training process for the an4 demo. Worked on generating the feature model for the TI Digit short test data. Sample output of a training process (it took more than 20 min to compile this code)

15. Temple University: Slide 14 Generating the feature vectors There two main step in generating the feature vector: 1. Generate the.Fileids file (it is just the path list of all the data file) 2. Modify the Make_feats (perl script) to in order to read the correct data in and change the default settings that the SphinxTrain comes with.

16. Temple University: Slide 15 Conclusion and Future The main problem in feature generation is that the Make_feats file has default settings for the an4 tutorial, hence to getting it working we have to change the configuration for both the make_feats file and the SphinxTrain connfig file (because the config file determines what goes in to the make_feats file. Follow the below Example )