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Robust ASR system : Malayalam

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Robust ASR system : Malayalam

  1. 1. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Robust ASR system : Malayalam Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Guided By : Mr.Edet Bijoy K Assistant Professor Department of ECE MES College of Engineering May 3, 2012ASR system : MalayalamCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust
  2. 2. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Objective To implement a digit recognizing prototype for Malayalam Language 0-9 using HMM model of speechCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  3. 3. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Contents 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  4. 4. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Contents 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  5. 5. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Contents 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  6. 6. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Contents 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  7. 7. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Contents 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  8. 8. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Contents 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  9. 9. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  10. 10. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion What is Speech? Produced when air from lungs passes through glottis, throat and mouth Excitation in three ways: Voiced excitation Unvoiced excitation Transient excitation Some sounds - Combinations of three excitations Spectral Changes - Vocal TractCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  11. 11. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion What is Speech? Produced when air from lungs passes through glottis, throat and mouth Excitation in three ways: Voiced excitation Unvoiced excitation Transient excitation Some sounds - Combinations of three excitations Spectral Changes - Vocal TractCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  12. 12. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion What is Speech? Produced when air from lungs passes through glottis, throat and mouth Excitation in three ways: Voiced excitation Unvoiced excitation Transient excitation Some sounds - Combinations of three excitations Spectral Changes - Vocal TractCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  13. 13. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion What is Speech? Produced when air from lungs passes through glottis, throat and mouth Excitation in three ways: Voiced excitation Unvoiced excitation Transient excitation Some sounds - Combinations of three excitations Spectral Changes - Vocal TractCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  14. 14. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Pictorial Representation of “SHOP”Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  15. 15. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Characteristics of Speech Bandwidth - 4 KHz Fundamental Frequency - Depends on the type of articulation Peaks in the Spectrum - Voiced excitation - P(f ) - Triangular Pulse Unvoiced excitation - a white noise generator Pitch Extraction: Rabiner Gold Pitch Tracker Autocorrelation Pitch TrackerCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  16. 16. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Pitch Extraction - AutocorrelationCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  17. 17. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Formant Frequency Concentration of acoustic energy on particular frequency At 1000 Hz intervals Resonance in Vocal Tracts Spectrogram - Darkness: Strength of formantCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  18. 18. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion SpectrogramCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  19. 19. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Speech Production Model S(f ) = (v P(f ) + uN(f ))H(f )R(f ) = X (f )H(f )R(f ) The mixture between voiced and unvoiced excitation determined by v and u The fundamental frequency determined by P(f ) The spectral shaping determined by H(f ) The signal amplitude depending on v and uCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  20. 20. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion About Automatic Speech Recognition Automatic Speech Recognition - Advancing and challenging Most of the research works - English, Arabic, Mandarin Native Indian Languages - Minimal work Industry - AT & T, Nuance, IBM Open Source - Vox ForgeCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  21. 21. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion About Automatic Speech Recognition Automatic Speech Recognition - Advancing and challenging Most of the research works - English, Arabic, Mandarin Native Indian Languages - Minimal work Industry - AT & T, Nuance, IBM Open Source - Vox ForgeCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  22. 22. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion About Automatic Speech Recognition Automatic Speech Recognition - Advancing and challenging Most of the research works - English, Arabic, Mandarin Native Indian Languages - Minimal work Industry - AT & T, Nuance, IBM Open Source - Vox ForgeCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  23. 23. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion About Automatic Speech Recognition Automatic Speech Recognition - Advancing and challenging Most of the research works - English, Arabic, Mandarin Native Indian Languages - Minimal work Industry - AT & T, Nuance, IBM Open Source - Vox ForgeCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  24. 24. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion About Automatic Speech Recognition Automatic Speech Recognition - Advancing and challenging Most of the research works - English, Arabic, Mandarin Native Indian Languages - Minimal work Industry - AT & T, Nuance, IBM Open Source - Vox ForgeCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  25. 25. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Classifying ASR system System contains two subsystems: ASR - Transcribe natural speech SU - Understand the meaning of transcribed speech ASR system classified as: DVI - Direct Voice Input LVCSR - Large Vocabulary Continuous Speech RecognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  26. 26. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Block Diagram of ASR Acoustic Properties - Linguistic representation Initial acquisition - Signal transduction or Recording Feature extraction - Spectral Analysis Segmentation - Phoneme Boundary RecognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  27. 27. Introduction Implementation Methodology Speech HTK Implementation Automatic Speech Recognition Analysis and Result Components of ASR Future Work Approaches of ASR Conclusion Approaches of ASR Template Based Approach Knowledge Based Approach Statistical Approach Conversational Recognition Recognition using Learning Approach Artificial Intelligence in RecognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  28. 28. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  29. 29. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion Implementation Challenges Successive Recognition - Artificial Pauses Continuous speech recognition - Co Articulation Physiological parameters Prosody and Temporal featuresCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  30. 30. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion Database Preparation Most important phase for training and recognition accuracy 50 people - 25 males and 25 females 10 words repeated 20 time each 10000 words for training 35 speakers used for training and 15 reserved for recognition Utterances converted to Cepstral domain Optimization for HMM parameter determinationCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  31. 31. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion Feature Extraction Temporal - SPEAKER Recognition Spectral - SPEECH Recognition Critical band filter Cepstral Analysis N−1 S(k) = s(n)exp((−j2π/N)nk) (1) n=0 ˆ S(k) = log (S(K )) (2) N−1 ˆ S(n) = 1/N ˆ S(k)exp((−j2π/N)nk) (3) k=0Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  32. 32. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion MFCC Fourier of a windowed signal Map power of spectrum on mel scale Logs of power at each mel DCT Amplitude - MFCC Normalising Raising log mel amplitudes to higher powersCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  33. 33. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion MFCC for HTK Usually static Performance - Time derivative Delta D Acceleration A Third Differential Suppress Absolute energy - Optionally Vocal Tract Length Normalisation (VTLN)Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  34. 34. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion HMM for isolated word recognition In normal method - Isolated word concatenation Recognizer map between sequences of speech vectors and symbol sequences But one to one mapping complex as underlying sequences produce similar sounds Boundaries between symbols cannot be identified explicitly Sequence of speech vectors corresponding to each word generated by a Markov model A Markov model is a finite state machine which changes state once every time unitCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  35. 35. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion A Markov Generation Model Bayesian Interpretation - Finite State Bayesian model with Markovian prior Θ∗ = ArgMax P(Θ) P(S|Θ)P(Y |S, Θ) (4) Θ s∈SCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  36. 36. Introduction Implementation Methodology Implementation Challenges HTK Implementation Database Preparation Analysis and Result Feature Extraction Future Work HMM Implementation Conclusion HMM for isolated word recognition Modeling of HMM - HTK Six state model moves through the state sequence X = 1, 2, 2, 3, 4, 4, 5, 6 to generate the sequence o1 to o6 P(O, X | M) = a12 b2 (o1 )a22 b2 (o2 )a23 b3 (o3 )...Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  37. 37. Introduction Implementation Methodology HTK Implementation What is HTK? Analysis and Result HTK Familiarisation Future Work Conclusion 1 Introduction Speech Automatic Speech Recognition Approaches of ASR 2 Implementation Methodology Implementation Challenges Database Preparation Feature Extraction 3 HTK Implementation What is HTK? HTK Familiarisation 4 Analysis and Result 5 Future Work 6 ConclusionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  38. 38. Introduction Implementation Methodology HTK Implementation What is HTK? Analysis and Result HTK Familiarisation Future Work Conclusion What is HTK? HMM Toolkit Cambridge University - Initially by MS Used for OCR, WSN and Speech Recognition 39 tools and customized tools ... Variety of options: Time limitation, thus only default used PortableCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  39. 39. Introduction Implementation Methodology HTK Implementation What is HTK? Analysis and Result HTK Familiarisation Future Work Conclusion HTK Familiarisation Tools Function HParse Parsing using Backus Naur HDMan Dictionary Creation of HTK format HLEd MLF file Manipulation HCopy Feature Extraction - Acoustic Analysis HCompV HMM prototype creation HRest Training - Baum Welch HHed HMM manipulation HVite Viterbi -Decode HResult Gives the resultCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  40. 40. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Analysis and Result 50 types of database - 25 training and 25 Testing 35 training and 15 testing Speaker dependent - 90% Speaker Independent - 83%Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  41. 41. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Confusions Numbers Confusion 1 0 3 1 3 2 - 3 1 4 - 5 - 6 - 7 8 8 7 9 - START SIL - END SIL -Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  42. 42. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Future Work Extended word recognition system MS SDK Acoustic unstable field System can be easily adopted to Continuous Speech Real time recognition Blocksets to existing toolsCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  43. 43. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Future Work Extended word recognition system MS SDK Acoustic unstable field System can be easily adopted to Continuous Speech Real time recognition Blocksets to existing toolsCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  44. 44. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Future Work Extended word recognition system MS SDK Acoustic unstable field System can be easily adopted to Continuous Speech Real time recognition Blocksets to existing toolsCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  45. 45. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Future Work Extended word recognition system MS SDK Acoustic unstable field System can be easily adopted to Continuous Speech Real time recognition Blocksets to existing toolsCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  46. 46. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Future Work Extended word recognition system MS SDK Acoustic unstable field System can be easily adopted to Continuous Speech Real time recognition Blocksets to existing toolsCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  47. 47. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Future Work Extended word recognition system MS SDK Acoustic unstable field System can be easily adopted to Continuous Speech Real time recognition Blocksets to existing toolsCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  48. 48. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  49. 49. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  50. 50. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  51. 51. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  52. 52. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  53. 53. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  54. 54. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  55. 55. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Conclusion Speech - Technical approach ASR Approaches Challenges Feature Extraction HTK Familiarization Inaccuracy - Lack of Database Extended digit recognitionCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  56. 56. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion AppendixCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  57. 57. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Mel Scale and Cepstrum Convert Hz to Mel f f m = 2529log10 1 + = 1127loge 1 + (5) 700 700 Gunnar Fant proposed 1000 f m= log10 1 + (6) log2 1000Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  58. 58. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Real time understanding of HMM Evaluate - Forward Algorithm Decode - Viterbi Train - Baum WelchCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  59. 59. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion HMM ExampleCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  60. 60. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Viterbi ExampleCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  61. 61. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Baum Welch Generalized Expectation-Maximization (GEM) algorithm Maximum Likelihood Estimates Posterior Mode Estimate Transition and Emission probabilities Dividing the expected transition from Si to Sj by the expected transitions from SiCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  62. 62. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Frequency Warping Performed by applying the unitary warping operator U One spectral representation on a certain frequency scale and with a certain frequency resolution transformed to another representation on a new frequency scale Resolution uniform on the new scale - Non-Uniform with respect to old scale Scale transform of a function ∞ e −j2πlnf DX (c) = X (f ) √ df (7) 0 fCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  63. 63. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion Inverse scale-transform ∞ ∞ √ e −2πclnf DX (c) = αX (αf ) √ df = e j2πlnα DX (c) (8) 0 fCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  64. 64. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion MLE Maximum Likelihood Estimation Value of parameter vector maximizing the probability Searching the multi-dimensional parameter space MLE EstimateCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  65. 65. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion References [1 ] Claudio Bechetti and Klucio Prina Ricotti, Speech Recognition Theory and C++ Implementation, John Wiley and Sons, pp. 10, 2004. [2 ] Davis K. H., Biddulph R. and Balashek S, Automatic Recognition of Spoken Digits, Journal of Acoustical Society of America, Volume:24, Issue:6, pp. 637-642, 1952. [3 ] Rabiner, L., R., Wilpon, J. G., Considerations in applying clustering techniques to speaker-independent word recognition, Journal of Acoustical Society of America,Volume:66, Number:3, pp. 663-673. 1979. [4 ] Mori R.D, Lam L, Gilloux M., Learning and plan refinement in a knowledge based system for automatic speech recognition,IEEE Transaction on Pattern Analysis Machine Intelligence, Volume 9, Number 2, pp.289-305, 2001. [5 ] Huang, C., Tao, C., Chang,E., Accent Issues in Large Vocabulary Continuous Speech Recognition, International Journal Of Speech Technology, Volume:7, pp.141-153, 2004 [6 ] Steve Young et. al.,The HTK Book(for HTK Version 3.4),Cambridge University Engineering Department, pp.3-6, 2009 [7 ] E. J. Candes,Compressive sampling,Proceedings of International Congress of Mathematicians, 2006 [8 ] S. F. Cotter,Sparse Representation for accurate classifi cation of corrupted and occluded facial expressions ,Proceedings of ICASSP, pp. 838-841, 2010Carrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
  66. 66. Introduction Implementation Methodology HTK Implementation Analysis and Result Future Work Conclusion “A technology is a real progress when it is available to anyone”- Henry Ford THANK YOUCarrol Xavier, Mohammed Musfir, Rahmathulla, Supriya, Yasif Robust ASR system : Malayalam
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