BUILD AI APPLICATIONS
Research and evaluation methods for language, vision, speech, and document AI. Start with a test plan you can repeat.
BUILD AI / ARTICLES
Explore evaluations and practical methods across AI application topics.
LLM evaluation ·
A practical test plan for multilingual AI: choose representative languages, separate translation from cultural knowledge, measure task quality, and inspect failures.
Speech processing ·
A reproducible checklist for comparing speech recognition systems with word error rate, language slices, streaming latency, and real-world audio.
Computer vision ·
A practical image captioning evaluation plan covering factual accuracy, missing details, accessibility, and human review.
Document AI ·
Measure OCR text accuracy and downstream field extraction across scans, layouts, languages, and confidence thresholds.
Speech processing ·
Compare synthetic speech with listening tests, pronunciation checks, latency, stability, and language-specific slices.
Speech processing ·
Design audio classification tests with class balance, macro F1, confusion analysis, and real recording conditions.
Speech processing ·
Evaluate VAD with missed speech, false alarms, boundary timing, and downstream transcription impact.
LLM evaluation ·
A reproducible checklist for retrieval-augmented generation, from evidence recall to grounded answers and failure review.
Computer vision ·
Compare image embeddings using relevant-item labels, recall at k, ranking quality, latency, and dataset slices.
LLM evaluation ·
Compare serving stacks with identical workloads, time to first token, token latency, throughput, and cache controls.
Vision & document AI ·
Retrieval-Augmented Generation (RAG) models have transformed how information is extracted and generated from PDFs.
Vision & document AI ·
Image captioning technology is transforming AI-driven interactions by enabling automated and highly accurate image descriptions.
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