This article deeply examines the source code of Go’s high‑performance segmentation library gse, revealing its Double‑Array Trie, shortest‑path dynamic programming, and HMM‑Viterbi implementations, and demonstrates practical usage for Chinese tokenization, part‑of‑speech tagging, keyword extraction, and custom dictionary management.
This article explains Hidden Markov Models, covering their core concepts, basic elements, the three fundamental problems with forward, Viterbi, and Baum‑Welch algorithms, provides a weather illustration, detailed Python code using hmmlearn, and a real‑world earthquake case study, highlighting practical implementation steps.
This article explains the background, evaluation metrics, and technical framework of computer‑assisted language learning, detailing how modern AI‑driven speech assessment systems use HMM‑DNN models, GOP scoring, conformer architectures, streaming solutions, and edge‑cloud deployment to deliver accurate, low‑latency pronunciation feedback for learners.
This article provides a comprehensive overview of sequence labeling tasks in NLP, covering their definition, common tag schemes (BIO, BIEO, BIESO), comparisons with other NLP tasks, major modeling approaches such as HMM, CRF, RNN and BERT, real‑world applications like POS tagging, NER, event extraction and gene analysis, and a step‑by‑step PyTorch implementation with dataset preparation, training pipeline, and evaluation metrics.
This article explores how large‑scale trajectory mining can overcome the timeliness limits of traditional street‑sweeping data collection, detailing the underlying principles, technical challenges such as vehicle‑type detection and map‑matching, and practical solutions ranging from rule‑based filters to advanced AI models.
This article systematically explains the key technologies behind mobile and vehicle navigation positioning, covering sensor fusion, AHRS, map‑matching algorithms based on hidden Markov models, Kalman filtering, and the evolution toward lane‑level and centimeter‑level accuracy for autonomous driving.
Road matching, a core subset of map‑matching theory, aligns GPS points to the correct road segments using algorithms such as distance‑based measures, Fréchet‑distance global optimization, and Hidden Markov Models, enabling accurate navigation, heterogeneous data fusion, traffic analysis, and urban planning, as validated by ACM SIGSPATIAL competitions.
Baidu’s speech synthesis system, developed since 2013 to give machines natural Chinese voices, tackles millions of tonal variations through phonetic compression and optimized acoustic models, balances trade‑offs in data and scalability, and offers a free open platform that lets developers integrate high‑quality text‑to‑speech into apps, advancing equal access to information.
