Course Content
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Day 01 - Module 1 Computer Speech Processing 0/3
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Overview of the courseLecture1.1
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A Brief history of speech processingLecture1.2
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The progress in three decades of research.Lecture1.3
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Module-2 Speech Sounds 0/3
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Physiology of speech production;Lecture2.1
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A model for speech productionLecture2.2
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Types of soundsLecture2.3
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Module-3 Speech Processing 0/3
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Feature extractionLecture3.1
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Linear predictive coding;Lecture3.2
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Cepstral coefficients.Lecture3.3
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Module-4 Classification & Machine Learning 0/3
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Classification of static vectorsLecture4.1
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Popular classifiers in machine learning;Lecture4.2
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Bayes decision ruleLecture4.3
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Day 02 - Module-1 Multivariate Distributions 0/3
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Distributions for modeling acoustics;Lecture5.1
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ML parameter estimationLecture5.2
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Gaussian mixture models.Lecture5.3
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Module-2 Elementary Pattern Recognition 0/4
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Template matchingLecture6.1
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Dynamic programmingLecture6.2
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Dynamic time warpingLecture6.3
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Morphing dynamic time warping to hidden Markov models.Lecture6.4
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Module-3 HMM Parameter Estimation 0/2
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EM algorithm for HMMLecture7.1
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Viterbi algorithm.Lecture7.2
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Module- 5 Finite State Machines 0/3
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Day 03 - Module-1 Basic ASR Systems 0/5
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Increasing the complexity in stepsLecture9.1
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Context-independent to context-dependent acoustic models;Lecture9.2
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Gaussian mixture splittingLecture9.3
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Multistage searchLecture9.4
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Simple methods for system combinationLecture9.5
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Module-2 Distribution Clustering 0/3
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Need for context-dependent models;Lecture10.1
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Clustering distributionsLecture10.2
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Decision tree based state clustering; from decision tree to transducers.Lecture10.3
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Module-3 Discriminative Training 0/3
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Module-4 Speaker Adaptation 0/6
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Bridging the gap between SI and SD systemsLecture12.1
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Types of adaptation – speaker adaptive training and speaker adaptationLecture12.2
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MLLRLecture12.3
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constrained MLLRLecture12.4
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Regression classLecture12.5
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MAP.Lecture12.6
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Day 04 - Module-1 Feature Space Normalization 0/3
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Vocal tract length normalizationLecture13.1
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All pass transformLecture13.2
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Maximum likelihood linear transform under different constraints.Lecture13.3
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Module-2 Large Vocabulary ASR 0/3
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Sketch of a state-of-the-art LV-ASRLecture14.1
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Cross adaptationLecture14.2
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System combination.Lecture14.3
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Module -3 Advanced Topics 0/4
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Overview of robust ASR techniquesLecture15.1
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Non-parametric techniquesLecture15.2
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Utterance classificationLecture15.3
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Detecing para-/extra-linguistic features in speech.Lecture15.4
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