When AI speech-to-text struggles with dialects and accents, do not conclude the tool is useless: most of the time the language setting, recording quality, and speaking style are misaligned, and fixing them visibly lifts accuracy.
First: language and dialect settings
Confirm whether the transcription tool is set to Mandarin or to the relevant dialect. Many tools default to Mandarin only, so forcing dialect content through a Mandarin model is naturally inaccurate. For tools that support dialects, switch manually to the right dialect option; for tools that do not, run a first pass with a product strong at dialect transcription, then proofread with a general tool.
Second: recording quality
Distance, noisy surroundings, and several people talking at once all drag accuracy down. Keep the speaker close to the microphone, switch off background TV and music, let one person speak at a time, and listen to the recording first to confirm the voice is clear before transcribing. Phone recordings and far-end conference room pickup are inherently hard material; do not demand perfect accuracy from them.
Third: speaking style and post-editing
Fast speech, swallowed syllables, and many technical terms all invite guessing. Before transcribing, ask speakers to slow down slightly and say technical terms in full the first time. After transcription, do not use the text as-is; listen against the original, focusing proofreading on the four categories most prone to error: people's names, place names, numbers, and technical terms. If one passage keeps failing, cut it out and transcribe it separately, or handle that passage with a different tool that supports the dialect.
Check three capabilities before choosing a tool
Before choosing a transcription tool, check three capabilities: whether it supports the dialect you need, whether it separates multiple speakers, and whether it exports text with timestamps. Dialect support decides whether it is usable at all, speaker separation decides whether multi-person meeting notes can be attributed correctly, and timestamps decide whether proofreading can jump quickly to the original audio. All three are indispensable; judging by advertised accuracy figures alone easily leads to a wrong purchase.
