- benchmark.py: measure RSS delta via /proc/self/status before/after each
transcription; add ram_mb field to BenchRow
- gtksettings.py: add RAM (MB) column to results table (index 8); tooltip
column shifted to index 10
- CHANGELOG.md: full history from v2.02.00 through v2.03.01
- README.md: benchmark description updated to mention RAM column
- MANUAL.md: benchmark result columns as table; Log tab documents
level filter dropdown
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- stt.py: add ModelMeta dataclass, fmt_languages(), list_models_meta(),
detect_remote_device(); refactor list_models() to delegate
- benchmark.py: add languages field to BenchRow; fetch via _get_langs()
with URL-level caching using list_models_meta()
- gtksettings.py: show language labels per engine in checkbox list;
add language codes to search filter; add Lang column to results table
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- stt.detect_remote_device(): probes /info (faster-whisper-server) then
/metadata (NVIDIA NIM) to detect CUDA vs CPU; cached per unique URL
- BenchRow gains url field; Device column now shows "CUDA" for GPU remotes
instead of the generic "remote"
- Benchmark table gains URL column (scheme stripped, max 180px wide)
- "Test all models per engine" checkbox: fetches list_models() for each
remote engine and expands to one row per model when checked
- benchmark.run() gains expand_models parameter
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- BenchRow gains `best_for` field: "Short clips" / "Short / medium" /
"Long / batch" / "Streaming" — derived from engine type and model name
- Device now shows "CUDA" instead of "GPU" for clarity
- Benchmark table gains a "Best for" column between Device and Time(s)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- BenchRow gains a device field; Transcriber records its resolved device, so
local engines report CPU or GPU and remote engines show "remote". New Device
column in the results table.
- Accuracy is now case-sensitive by default (capitalisation counts) so an
all-lowercase transcript no longer scores 100%. Punctuation is still ignored.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
New benchmark.py: word-error-rate accuracy + a run() that times each STT engine
on a reference clip. Settings gains a Benchmark tab: pick a .wav and a matching
.txt, run all STT engines, see Time + Accuracy per engine and a summary of the
fastest and most accurate. Add presets for each model you want compared.
Fix "Local engine selected but the model isn't loaded." on Test: a cached
_transcriber_for() loads the local model on demand (the daemon only preloads it
when a local engine is active). Tested: local small 2.17s/100% vs remote :8010.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
