ElevenLabs says speech-to-text accuracy can mostly be fixed with configuration adjustments
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In its blog, ElevenLabs states that speech-to-text accuracy mainly depends on three types of factors: audio input quality, speaker dynamics, and vocabulary context. Most issues can be fixed by adjusting existing configurations or recording methods, without changing model settings. It recommends recording at a 16 kHz or higher sample rate in a lossless format, placing the microphone four to six inches from the speaker, and using voice isolation, speaker diarization, or multi-channel recording to handle noise and overlapping speech; accuracy is measured by word error rate (WER), and priority should be given to the types of errors with the greatest business impact. The above are ElevenLabs' claims, not proven results.
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- ElevenLabs BlogFix speech to text accuracy problems with a smarter workflow
This guide explains that speech to text accuracy depends on audio input quality, speaker dynamics, and lexical and contextual issues, and that fixes should target the input, processing, or output stage of the pipeline. It recommends recording at 16 kHz or higher in lossless formats with microphones four to six inches from the speaker, using voice isolation, diarization or multichannel recording, and keyterm prompting, and measuring accuracy with word error rate. It also notes that ElevenAPI offers Scribe v2 with keyterm prompting, multichannel transcription, and speaker diarization.
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