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We propose a novel procedure to generate pseudo mandarin speech data named asCAMP (character audio mix up), which aims at generating audio from a characterscale. We also raise a method for building a mandarin character scale audiodatabase adaptive to CAMP named as META-AUDIO, which makes full use of audiodata and can greatly increase the data diversity of the database. Experimentsshow that our CAMP method is simple and quite effective. For example, we trainmodels with 10 hours of audio data in AISHELL-1 and pseudo audio data generatedby CAMP, and achieve a competitive 11.07 character error rate (CER). Besides,we also perform training with only 10 hours of audio data in AIDATATANG datasetand pseudo audio data generated by CAMP, which again achieves a competitive8.26 CER.

10 hours data is all you need