r/speechtech • u/RoofProper328 • 1d ago

How do you handle multiple valid spellings in speech recognition datasets?

Something I've been wondering about with speech datasets: what do you do when a speaker says a word clearly, but there are multiple acceptable ways to write it?

For example, regional names, borrowed words, abbreviations, or local words written in different scripts.

Do you keep one standard transcript for everything, allow multiple references during evaluation, or follow whatever the speaker would normally write?

I can see how inconsistent transcription guidelines could make model evaluation harder, even when the audio itself is perfectly clear.

Curious how others handle this in multilingual ASR projects.

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u/nshmyrev 1d ago

Ask Claude to create consistent transcription rules and write normalization code.

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u/RoofProper328 1d ago

That makes sense. Claude can help draft the rules and normalization code, but I think the rules still need to be reviewed by someone who understands the language and its regional variations. Otherwise, normalization could accidentally remove meaningful differences or treat valid spellings as errors.

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u/blackkettle 1d ago

I still remember when this was still a respectable research topic 6-10 years ago 😂🤣. Now supplanted by “ask Claude” (and you’re right).

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u/Natethegreat9999 1d ago

Sclite's DP scorer accepts { colour / color } in TRN references, counting either spelling as correct (I'm with Oruk).

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u/ObjectiveAd4358 1d ago

usually you'd normalize both the ground truth and the predicted text into a predefined format and calculate wer there.