A look at the models, datasets and evaluation practices that shaped 2000s research in speech recognition, computer vision and medical imaging.
How Language Identification Worked in the 2000s
A look at mid-2000s speech language identification: acoustic and phonotactic models, score fusion, low-resource languages, and the limits of evaluation.
Document Processing in the Mid-2000s: Beyond OCR
How mid-2000s document systems combined image cleanup, layout analysis, OCR, field extraction, and human review to turn scanned pages into usable records.
How Statistical Methods Changed Speech Synthesis in the 2000s
A look at 2000s speech synthesis: how unit selection and HMM-based voice models worked, why they sounded different, and what listening tests revealed.
How Conferences Shaped AI Research in the 2000s
A look at how 2000s AI conferences shaped benchmarks, methods and publication practices across speech, vision and machine learning.
Object Tracking in the 2000s: Motion, Occlusion, and Identity
How 2000s visual trackers predicted motion, handled occlusion, matched detections, and measured identity errors across video frames.
What Small Speech Corpora Could—and Couldn’t—Show in the 2000s
How 2000s speech researchers built and tested recognizers for under-resourced languages, from acoustic transfer and lexicons to careful evaluation.
Machine Learning in 2000s Recognition Research: Features, Models, and Evaluation
How 2000s researchers combined designed features and learned models in speech, vision, and document analysis—and tested whether their results generalized.
How AI Conferences Shaped Research in the 2000s
How 2000s AI conferences helped researchers compare results, share methods across fields, and expose the limits of benchmarks and published papers.
Beyond OCR: How 2000s Systems Learned to Read Page Structure
How mid-2000s document analysis moved beyond OCR to handle page layout, reading order, tables, forms and verifiable extraction.