Prasa Tech Chronicles

A historical look at speech recognition evaluation: word error rate, transcript conventions, shared test sets, and why scores from different tasks need context.

How early speech researchers built recognizers with limited data, from multilingual acoustic models to local transcription, text, and testing decisions.

How phonetics, pronunciation dictionaries, transcripts, prosody, and language-specific analysis shaped speech recognition and synthesis in the mid-2000s.

A guide to mid-2000s speech research: recording conditions, shared evaluations, language coverage, synthesis, and the details behind reported results.

A look at OCR, page layout, and mid-2000s document-analysis research—and why searchable text still needs a link to the original page.

Explore how speech science, statistics, engineering, and careful benchmarks shaped recognition research through the mid-2000s.

Trace object recognition research from perception and geometric models to statistical classifiers and mid-2000s benchmarks, with a guide to comparing early results.

A look at geometric models in early AI: how they described shapes, matched views, supported vision tasks, and met the limits of real images.

How speech systems detect language switches, from 2000s acoustic and phone-based methods to neural models—and why boundary-aware evaluation matters.

A history of multilingual speech recognition, from language routing and shared acoustic models to neural training, code-switching, and fair evaluation.