PPT-ECE 417, Lecture 11: MFCC

Mark HasegawaJohnson 1022018 Content What spectrum do people hear The basilar membrane Frequency scales for hearing mel scale Melfilter spectral coefficients also called filterbank. The problem is that this information is oftenly unknown LMS is a method that is based on the same principles as the met hod of the Steepest descent but where the statistics is esti mated continuously Since the statistics is estimated continuously th Machine Learning. April 15, 2010. Today. Adaptation of Gaussian Mixture Models. Maximum A Posteriori (MAP). Maximum Likelihood Linear Regression (MLLR). Application: Speaker Recognition. UBM-MAP + SVM. 11. Assembly Language and . Arduino. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded into the . (and how . Kaldi. works). Overview of this talk. Will be going through the process of downloading . Kaldi. and running the Resource Management (RM) example.. Will digress where necessary to explain how . CS4706. Fadi. . Biadsy. 1. Outline. Speech Recognition. Feature Extraction. HMM. 3 basic problems. HTK. Steps to Build a speech recognizer. 2. Speech Recognition. Speech Signal to Linguistic Units. Assembly Language and . Arduino. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded into the . Cepstral. Coefficients. Lecture . 7. Spoken Language Processing. Prof. Andrew Rosenberg. Representing Acoustic Information. 16-bit samples 44.1kHz sampling rate. ~. 86kB/sec. ~5MB/min. Waves repeat. AswiththeAfricanelephantexperiments,multipleexperimentalsetupsareimplemented,includingcaller-independent(CI),rank-dependent(RD),age-dependent(AD),gender-dependent(GD)andcaller-dependent(CD).Evaluation References. : 1. 3.3, 3.4 of Becchetti. 3. 9.3 of Huang. Waveform plots of typical vowel sounds - Voiced. （濁音）. tone. 1. tone 2. tone. 4 . t.  . (. 音高. ). Speech Production and Source Model. of articulation . in . unvoiced stops . with . spectro. -temporal surface . modeling . V. . Karjigi. . , . P. . Rao. Dept. of Electrical Engineering, Indian Institute of Technology Bombay, . Powai. , Mumbai 400076, India . Assembly Language and . Arduino. Behind the C code (or sketch). C provides. a somewhat human. -readable interface. but . it . gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded. Assembly Language and . Arduino. Adapted from T. Murphy’s slides. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. 11. Assembly Language and . Arduino. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded into the . Yu-Gang . Jiang. School of Computer Science. Fudan University. Shanghai, China. ygj@fudan.edu.cn. ACM ICMR 2012, Hong Kong, June 2012. S. peeded . Up. . E. vent . R. ecognition. ACM International Conference on Multimedia Retrieval (ICMR), Hong Kong, China, Jun. 2012..