Speech Recognition

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Speech Recognition

  1. 1. Speech Recognition for Control Hugo Moreno ESPOCH-ECUADOR IEEE Member
  2. 2. AGENDA <ul><li>Introduction </li></ul><ul><li>Speech Recognition </li></ul><ul><li>Application in Control </li></ul><ul><li>Conclusions </li></ul>
  3. 3. Introduction                                                                                                            
  4. 4. Introduction <ul><li>VISION </li></ul><ul><li>To be a leading institution in the Top Education and in the scientific and technological support for the socioeconomic and cultural development of the province of Chimborazo and of the country, with quality, relevancy and social recognition </li></ul>
  5. 5. Speech Recognition <ul><li>speaker recognition </li></ul><ul><ul><li>recognizing who is speaking </li></ul></ul><ul><ul><li>frequencies </li></ul></ul><ul><li>speech recognition </li></ul><ul><ul><li>recognizing what is being said </li></ul></ul><ul><li>accuracy and speed </li></ul>
  6. 6. Speech Recognition <ul><li>The process of converting a speech signal to a sequence of words in the form of digital data or discrete data, by means of an algorithm implemented as a computer program (microcontroller) . </li></ul>
  7. 7. Speech Recognition <ul><li>Speech Signal Acquisition </li></ul><ul><ul><li>LPF – AB = 4KHz </li></ul></ul><ul><ul><li>8Ks/s </li></ul></ul><ul><ul><li>8-16 bits </li></ul></ul><ul><li>Speech Verification </li></ul><ul><ul><li>feature extraction and selection, </li></ul></ul><ul><ul><ul><ul><li>Poles and Zeros </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Correlation </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Levinson – Durbin </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Markov (HMW) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>DTW </li></ul></ul></ul></ul><ul><ul><li>pattern matching, </li></ul></ul><ul><ul><li>classification. </li></ul></ul>
  8. 8. Speech Recognition Correlation (MATLAB) Signal Acquisition Original Pattern
  9. 9. Speech Recognition Poles and Zeros (MATLAB) Signal Acquisition Original Pattern
  10. 10. Application in Control <ul><li>Elevator </li></ul>
  11. 11. Application in Control <ul><li>Speech Biometric Recognition </li></ul>Used to determine the stress status. Stress Control using a special kind of music.
  12. 12. Application in Control <ul><li>Control for Robot </li></ul><ul><li>Automatic translation </li></ul><ul><li>Automotive speech recognition </li></ul><ul><li>Court reporting (Realtime Voice Writing) </li></ul><ul><li>Speech Biometric Recognition </li></ul><ul><li>Hands- free computing </li></ul><ul><li>Home automation </li></ul><ul><li>Pronunciation evaluation in computer-aided language learning applications </li></ul><ul><li>Transcription (digital speech-to-text). </li></ul>
  13. 13. Conclusions <ul><li>Speech recognition involves the ability to match a voice pattern against a provided or acquired vocabulary </li></ul><ul><li>Speech recognition is used to make control </li></ul><ul><li>Speech recognition has an acceptable accuracy, but better accuracy implies less speed. </li></ul>
  14. 14. References <ul><li>IEEE SIGNAL PROCESSING MAGAZINE </li></ul><ul><li>PROCEEDINGS OF THE IEEE </li></ul><ul><li>WANG Ye-Yi,Deng Li and Acero Alex, Spoken Language Understanding, IEEE SIGNAL PROCESSING MAGAZINE [16] SEPTEMBER 2005. </li></ul><ul><li>CAMPBELL JOSEPH P. Speaker Recognition: A Tutorial, PROCEEDINGS OF THE IEEE, VOL. 85, NO. 9, SEPTEMBER 1997 </li></ul><ul><li>DENG Li, Wang Kuansan and Chou Wu, Speech Technology and Systems in Human-Machine Communication, IEEE SIGNAL PROCESSING MAGAZINE [12] SEPTEMBER 2005 </li></ul>
  15. 15. <ul><li>Thanks for your attention .. </li></ul><ul><li>Best Regards </li></ul>Hugo Moreno oswaldo _m@ ieee . org ESPOCH-ECUADOR IEEE Member

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