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Typo fixes in documentation [skip ci]

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dscripka 2023-03-04 23:58:12 -05:00
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docs/synthetic_data_generation.md
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@ -22,4 +22,4 @@ Beyond the inherent ability of Waveglow and VITS to produce variable speech, the
1) Relatively high values are used for sampling parameters (which results in more variation in the generated speech) even if this causes low quality or incorrect generations some small percentage of the time.
2) To go beyond the original number of speakers used in multi-speaker datasets, [spherical interpolation](https://en.wikipedia.org/wiki/Slerp) of speaker embeddings is used to produce mixtures of different voices to extend beyond the original training set. While this occassionaly results in lower quality generations (in particular a gravely texture to the speech), again the benefits of increased generation diversity seem to be more important for the trained openWakeWord models.
2) To go beyond the original number of speakers used in multi-speaker datasets, [spherical interpolation](https://en.wikipedia.org/wiki/Slerp) of speaker embeddings is used to produce mixtures of different voices to extend beyond the original training set. While this occasionally results in lower quality generations (in particular a gravely texture to the speech), again the benefits of increased generation diversity seem to be more important for the trained openWakeWord models.