125 lines
6.9 KiB
Markdown
125 lines
6.9 KiB
Markdown
# Local spoken passages
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Google EmbeddingGemma 2 remains the semantic model for text, images, audio and
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video. An isolated local whisper.cpp worker adds recognized text to the same
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Google index. It does not replace raw audio evidence or introduce a hosted
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embedding backend.
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The service covers an audio track with contiguous windows of at most thirty
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seconds, overlapping by two seconds. Live Silero detection resets per window;
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multilingual base recognition uses DTW token points. This differs from the
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historical whole-source diagnostic in [SPEECH-DTW.md](SPEECH-DTW.md). Its 6/8
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timing score cannot be carried over to this implementation.
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Recognized passages retain source start/end points and exact recognized UTF-8.
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A point span can have zero duration. The UI starts playback at the estimated
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start and explains recognition uncertainty in the small match detail. A source
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point is not a verified complete utterance boundary.
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Raw Google media and recognized speech have independent completion policies.
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Adding or retrying recognition reuses compatible raw vectors. Optional speech
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failures preserve raw search evidence and report partial coverage. Excerpts
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require current source bytes/revisions and the issued recognized passage;
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same-stat overwrites invalidate them. CLI, UI and MCP use this shared behavior.
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Desktop setup downloads and verifies approximately 149 MB of base/VAD model
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data in addition to Google assets. Google query readiness stays independent.
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The native worker is shipped in an isolated runtime directory. Normal packages
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require both acceleration and CPU support; Windows VM execution is CPU only.
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Automatic retries use source revision and speech policy, preventing generation
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publication from creating an endless retry loop.
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Each native call uses one admitted background CPU thread. Detailed indexing
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metrics separate admission, decoding, VAD, model loading, ASR, transport and
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fallback cost. A running native call cannot be preempted by a foreground query
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on a one-thread budget. Raw media decoding and ANN work are outside this
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inference budget.
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## Evidence in this source change
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- Shared lifecycle, passage bounds, partial failures, provenance and policy
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tests passed. The complete workspace test command passed with genuine-model
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tests explicitly ignored pending their dedicated run.
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- Two genuine CPU FFmpeg tests passed: a two-second audio origin, an internal
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timestamp gap, seeks and tails preserve the source timeline.
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- Desktop Rust: 48 tests and strict Clippy passed. Frontend: 62 tests and
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formatting passed, including a stable partial-speech retry key.
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- The actual CLI speech setup verified/reused the pinned base and Silero cache.
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- Existing atomic staging tests passed; Windows package tests reject missing,
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changed, stale and internal CPU-only speech runtimes before replacing an
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existing archive.
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## Checks still required before delivery
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- [x] Current CPU native worker English/German context reuse and Unicode paths.
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- [x] Actual shared-service ASR plus Google lifecycle integration.
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- [x] Frozen independent four-file/ten-query and separate seam evaluation.
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- [ ] Normal hardware-detecting runtime staging and Windows package startup.
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- [ ] Publish/install the verified Windows update.
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- [ ] Native playback and graphical interaction, actual GPU execution, and
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other OS runtime checks.
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The independent fixture has no publisher phrase timestamps. It can measure
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retrieval and negative controls, but cannot establish precise word-level timing
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accuracy. Music relevance and general no-answer rejection remain separate open
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quality work; diagnostic integration alone does not raise the media rating.
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## Genuine CPU functional proofs
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The internal v3 worker SHA is
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`299c1b784eac46b31d228453a399e1378f327fc9ed5e34ab950c804da33e433a`;
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its inventory SHA is
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`4904995685a5e55e0a790d9cc409dc8458e39c30cda4097c5d70bf75cb5c976c`.
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English/German tests relocated the worker and real models to paths containing
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`München`, `測試` and `🚀`. Each repeated recognition returned stable bounded
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passages, and the second call reported zero additional model-load time. These
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checks selected `Auto` in the Rust client with `SEARCHI_FORCE_CPU=1`, so native
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execution was explicitly CPU. They do not validate dynamic acceleration loading.
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The actual service lifecycle test passed in 113.50 seconds. Adding recognition,
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an injected optional failure on policy upgrade, and a genuine retry all retained
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byte-identical raw Google vectors with zero additional raw-audio encodes.
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Recognized results, exact verified excerpts, stable policy/source retry identity
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and the retained Google query reader were checked. This uses a query derived
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from recognition to test the contract; it is not an independent relevance score.
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Raw log `.searchi/qa/service-speech-google-cpu-v3.log`: 1292 bytes, SHA
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`170700adf9315ae15ae3ab5a7df6a77ab01dc5b776be179c861d2461cfc48c03`.
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The first normal auto compilation reached Vulkan setup but failed on Windows
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nested MSBuild path length. Its log is retained, SHA
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`59f1820d6ac6adac6f525d8084c442c1ed261753eb34fcce916dc157041f777c`.
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An unchanged build in a shorter owned output directory is underway; no CPU-only
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distribution was substituted.
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The shorter-path normal auto build subsequently completed. Worker SHA
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`0b716fa17e8216ed46c7755d15acab20f658254b99780c7a68bab03d765c55bc`,
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inventory SHA
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`0e116c604141af147bd91736ec0722a0660dcda8c9da008e494c464753f4e5a1`.
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It contains private Vulkan/CPU backends, loader and matching Microsoft runtime
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files. The current normal artifact passed genuine repeated English recognition
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from Unicode paths with CPU forced. Fifty owned-process samples observed the
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CPU backend and no Vulkan modules; sampling alone does not prove absence at
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every instant. The pinned CPU-only loading branch complements that observation.
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See [runtime evidence](../tools/speech-runtime/README.md).
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## Frozen independent retrieval
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The four-file fixture retained both real English/German recordings, instrumental
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music and silence, plus all ten frozen queries. Six positive queries found a
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relevant file first, with recall@5 also 6/6. Music and silence produced zero
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accepted recognized passages. **All four absent queries still returned files.**
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The two readings share translated subject matter; this is a small file-retrieval
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test, not broad media accuracy or verified passage/word timing.
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Every expected window input and published citation passed source validation,
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including four windows across the two separate artificial seam sources.
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Transcription errors, partial boundary phrases and overlap duplicates remain in
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the evidence. Concept substring coverage is not a word-error score. Root
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independently recomputed the exact recorded scorer output.
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The complete report is 174868 bytes, SHA
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`79ecb75d31c0193642c81862fd5476ad47adca518d4959e436bdd472cc281798`.
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It uses the internal v3 CPU artifact and does not establish normal auto runtime
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quality parity or GPU performance. Details and the retained comparison are in
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[the evaluator](../tools/speech-eval/native-validation/README.md).
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