2. Speech recognition in mobile environment Robust ASR with dual Mic
UNIVERSITE D’ORAN 1
Ahmed Ben Bella
Speech recognition in mobile environment
Robust ASR with dual Mic
Présenté par :
Yacine IKKACHE
Encadré par :
Pr. Med SENOUCI
Dr. B KOUNINEF

3. WHAT IS ASR Command and control Automatic transcription
Automatic translation Home automation
Voice dialing

4. How its work

5. HMM-Based Recognizer pattern classification
Mathematical Formulation:

6. HMM-Based Recognizer pattern classification acoustic model

7. HMM-Based Recognizer pattern classification acoustic model

8. HMM-Based Recognizer pattern classification language model

9. HMM-Based Recognizer pattern classification search problem

10. Building Quran reader controlled by speech ASR with sphinx
Sphinx4 is a software implementation of HMM speech recognizer, it’s architecture is highly flexible

11. Acoustic model for Quranic reader data collection
Speech collection
We prepared a text file which contain 114 suras name’s, famous receiters names

12. Acoustic model for Quranic reader data collection
The audio file was recorded using a sampling rate of 16KHZ and 16 bit per sample
Each file has been named using this convention: speakername-commandID.wav
These audio files were divided into two sets

13. Building Quran reader controlled

14. Building Quran reader controlled

15. Publication
"Building Quranic reader voice interface using sphinx toolkit" in the Journal of American sciences (novembre 2013)
"Toward Quranic reader controlled by speech" in international journal of Advanced Computer Science & Application ( avril 2012)
The audio file was recorded using a sampling rate of 16KHZ and 16 bit per sample
Each file has been named using this convention: speakername-commandID.wav
These audio files were divided into two sets

16. Speech recognition in mobile environment

17. Speech recognition in mobile environment Architecture
The decision is driven by factors including device and network resources, ASR components complexity and application.

18. Speech recognition in mobile environment NSR
Coding
Transmission errors

19. Speech recognition in mobile environment DSR
The absence of coding and transcoding problems
Robustness against comm. channel & acoustic noise
Thin client, easy to update, no limits in ASR complexity
Front-end must be implemented in the device
Network dependency and transmission errors

20. Robust speech recognition on mobile environments.
Main research lines of the group:
Robust speech recognition on mobile environments.
Robust ASR on mobile devices with small microphone array.
Robust transmission of speech and video.
Ultrasonic non-destructive testing.
Signal processing in proteomics.

21. Robust speech recognition on mobile environments.

22. Robust speech recognition on mobile environments.

23. Robust speech recognition on mobile environments.

24. Robust speech recognition on mobile environments.

25. Robust speech recognition on mobile environments.

26. Robust speech recognition on mobile environments.

27. Robust speech recognition on mobile environments
Robust speech recognition on mobile environments. Noise reduction with single microphone

28. Robust speech recognition on mobile environments
Robust speech recognition on mobile environments. Noise reduction with dual Mic

29. Robust speech recognition on mobile environments
Robust speech recognition on mobile environments. Noise reduction with dual mic

30. Robust speech recognition on mobile environments
Robust speech recognition on mobile environments. Noise reduction with dual mic

31. Noise reduction with dual mic DNN to extract binary mask
Marginilization
Frame reconstruction

32. Noise reduction with dual mic DNN to extract soft mask
Y’= ES * Y1

33. Noise reduction with dual mic Dual Mic database creation

34. conclusion
Multichannel information can be exploited to improve ASR performance.
We are working on implementing novel technique ( DNN based soft mask estimation for robust ASR in Matlab )
The extracted features will be used in sphinx for recognition

35. Merci pour votre attention