W2_L3: Feature extraction for speech processing | part 01

Welcome to Week 2 Lecture 3 of the course "Speech Technology" by Profs. S. Umesh and Hema A. Murthy. Full Course: https://study.iitm.ac.in/ds/course_pages/BSEE4001.html Video Overview This lecture introduces the Gaussian distribution (bell curve) and its key parameters: mean (_) and variance (__). We’ll explore how Gaussian distributions model real-world data, such as height measurements, and discuss parameter estimation through Maximum Likelihood Estimation (MLE). Learn how to fit a Gaussian curve to your data and understand the concepts of likelihood, independence, and optimization using derivatives. The lecture also briefly touches upon pattern classification using Gaussians, setting the stage for feature extraction in speech processing. About IIT Madras' Online Bachelor of Science Programme IIT Madras offers four-year BS programmes that aim to provide quality education to all, irrespective of age, educational background, or location. The BS programme has multiple levels, which provide flexibility to students to exit at any of these levels. Depending on the courses completed and credits earned, the learner can receive a Foundation Certificate from IITM CODE (Centre for Outreach and Digital Education), Diploma(s) from IIT Madras, or BSc/BS Degrees from IIT Madras. For more details, Visit: https://www.iitm.ac.in/academics/study-at-iitm/non-campus-bs-programmes. #GaussianDistribution #NormalDistribution #BellCurve #Mean #Variance #StandardDeviation #MaximumLikelihoodEstimation #MLE #ParameterEstimation #StatisticalModeling #DataAnalysis #CurveFitting #Probability #Statistics #PatternClassification #SpeechProcessing #IITMadras #IITMadrasBS