  The Text Extraction of the Audio from the Video plays an important role in
multimedia editing and processing. As a popular open source toolkit, Whisper
performs fast in human voice recognition. However, the recognition performance
is dependent on the computing resource, which makes the low computing memory
running Whisper become difficult. Our paper presents an available solution to
extract the human voice from the video and gain the high quality text
generation from the voice. The generated voice can be used in video language
translation and translated voice simulation. To improve the extraction and
transform quality of human voice, we present ecVoice, a method using the idioms
similarity computation and analysis to improve the quality of audio text
extraction. Relative experiments are held to verify that the ecVoice can
improve the idiom grammar correction rate to 90\% on average. The method is
simple but fast which means this method will cause less bad influence of
consuming computing resources when improving the voice recognition rate. Our
method and solution can significantly enhance the Whisper recognition with low
computing memory.
