We want the Common Voice dataset to reflect the audio quality a speech-to-text engine will hear in the wild, so we’re looking for variety. In addition to a diverse community of speakers, a dataset with varying audio quality will teach the speech-to-text engine to handle various real-world situations, from background talking to car noise. As long as your voice clip is intelligible, it should be good enough for the dataset.
Di nsômbôl le mayaa ma Common Voice ma banga makiñ malam to ma ngi-bilama, ka i yé le nyum u u nhyelel kiñ matila u lak nok ndôñ i makiñ yosô kiki bôt ba mpémes mo yôha. Di yé di nyodi le basañge makiñ ba nlama ba nya yosô ikédé ngim loñ, di lela le, liyaa li makiñ li nlama bana mbuu makiñ, nya-ndi-nya, inyu ila niiga nyum u nhyelel makiñ matila le u meya ndôñ i makiñ yosô to hehoma mut a mpôdôl yo, to i ba yaa le liyôgha li yé, tole matôa a ñoñ mut bebee. I ntel u ñgéda nu kiñ yoñ i nnôôga, hala a kôli le i jôp i liyaa li makiñ.