Adolfo Reyna
36 lines
1.4 KiB
Plaintext
36 lines
1.4 KiB
Plaintext
# Fixes for words the recognizer gets wrong the same way every time.
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#
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# heard => replacement
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#
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# Matching is case-insensitive and word-bounded, so "coral voice" is rewritten
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# mid-sentence but "chorale" is left alone. Everything after a # is ignored.
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#
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# This is the blunt instrument, and that is the point: it is exact, testable,
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# and costs nothing at runtime. Vocabulary biasing (vocabulary.txt) is the
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# softer tool that stops the mistake happening at all — reach for that first,
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# and add a rule here only once you have seen the SAME wrong word more than
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# once. A rule is blind to context, so make each one specific enough that it
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# cannot fire on ordinary speech: prefer "coral voice" over bare "coral".
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#
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# These were observed in testing; delete any that don't match how you speak.
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# The two engines mishear differently, so both sets are here — the rules are
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# specific enough not to collide.
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# SpeechTranscriber (the default). Its errors are phonetically close, which is
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# what makes short rules like these enough.
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Kakoro => Kokoro
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Pipika => Pipecat
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Metemma => Metamate
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echo tale => echo tail
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graph QL => GraphQL
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# The older dictation model, used by --stt-engine apple and --analyzer-module
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# dictation. It fails further from the target, so it needs vocabulary biasing
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# as well as these.
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coral voice => Kokoro voice
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pit transport => Pipecat transport
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pipe cat => Pipecat
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LN point => endpoint
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fab ricator => Phabricator
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meta mate => Metamate
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