fix(asr): restore computer terminology bias
Rebuild the bundled language model and runtime source filtering around a dedicated computer-term corpus so technical dictation keeps domain coverage.
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@@ -1,7 +1,7 @@
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// BuiltinLexiconIndex.swift
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// OSGKeyboard · Shared
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//
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// In-memory index over the bundled project-curated AI/technology `phrases.tsv`.
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// In-memory index over bundled `phrases.tsv` (~10k computer terms).
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// macOS local ASR consumes a Top-N subset; the full index also backs
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// polish supplements and future retrieval.
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@@ -8,7 +8,7 @@ import Foundation
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public enum LocalASRBiasAdapter {
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/// Bundle IDs where the curated AI/technology vocabulary is especially likely.
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/// Bundle IDs where computer-science vocabulary is especially likely.
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private static let codeEditorBundleIDs: Set<String> = [
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"com.apple.dt.Xcode",
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"com.microsoft.VSCode",
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@@ -119,7 +119,7 @@ public enum LocalASRBiasAdapter {
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private static func preferredLexiconSources(for bundleId: String?) -> Set<String>? {
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guard let bundleId, codeEditorBundleIDs.contains(bundleId) else { return nil }
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return ["ai_tech_seed"]
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return ["computer_terms"]
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}
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private static func hardHotwordList(from terms: [String], maxCount: Int) -> [String] {
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