Advances in Large-Scale Multiple Sequence Alignment
Explore cutting-edge techniques in large-scale multiple sequence alignment, focusing on graph clustering, weighted consensus HMM, and phylogeny-aware methods for improved bioinformatics analysis.
Combined Stochastic Models for Cancer Patient Trajectories
Integrating diverse clinical data into a unified stochastic model for cancer patient trajectories, combining tumor growth, metastasis, and survival data using Julia for simulation and Bayesian inference.
Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models
Delve into high-dimensional mean estimation in binary Markov Gaussian mixture models, exploring how memory in data affects estimation error and the interplay between sample size, dimension, and signal strength.
Zipf's Law Suggests a Three-Pronged Approach to Inclusive Speech Recognition
Explore Zipf's law in speech recognition, from frequent words to OOV challenges. Discover how power-law distributions impact language technologies and inclusive ASR development for diverse communities.
OUCH: Investigating Limitations of Hidden Markov Models in Speech Recognition
Explore speech recognition challenges, focusing on Hidden Markov Model limitations. Examine frame-to-frame independence assumptions and their implications for improving recognition accuracy.
Tutorial on Hidden Markov Models - Part 2
Explore advanced concepts of Hidden Markov Models, including applications and algorithms, in this in-depth continuation of Jason Eisner's tutorial series.
UBM-based Acoustic Modeling for ASR - 2009
Explore advanced UBM-based acoustic modeling techniques for automatic speech recognition, enhancing ASR system performance and accuracy.
Speech Recognition - 2000
Explore fundamental concepts and techniques of speech recognition, including acoustic modeling, language modeling, and decoding algorithms.
Sequence Kernels for Speaker and Speech Recognition
Explore sequence kernels for speaker and speech recognition, focusing on generative kernels and their applications in feature extraction and classification using HMMs, GMMs, and SVMs.
An Implementation of Sub-Space Model Based Automatic Speech Recognition - 2009
Explore advanced speech recognition techniques using sub-space models in this in-depth implementation guide from Johns Hopkins University's CLSP.
Epigenomics and Hidden Markov Models in Computational Biology - Lecture 5
Explore epigenomics, histone modifications, and DNA profiling techniques. Learn about read mapping, quality control, and Hidden Markov Models for analyzing chromatin states in computational biology.
Part of Speech Tagging, Named Entity Recognition, and Hidden Markov Model
Master essential Natural Language Processing techniques including part-of-speech tagging, named entity recognition, and hidden Markov models for advanced text analysis.
Model Stealing for Low-Rank Language Models Through Reverse Engineering
Discover groundbreaking mathematical techniques for reverse-engineering language models through conditional queries and barycentric spanners, exploring MIT's innovative approach to model extraction.