The evaluation of sound level measuring mobile applications shows that the development of a sophisticated audio analysis framework for voice-recording purposes may be useful for journalists. In many audio recording scenarios the repetition of the procedure is not an option, and under unwanted conditions the quality of the capturing is possibly degraded. Many problems are fixed during post-production but others may make the source material useless. This work introduces a framework for monitoring voice-recording sessions, capable of detecting common mistakes and providing the user with feedback to avoid unwanted conditions, ensuring the improvement of the recording quality. The framework specifies techniques for measuring sound level, estimating reverberation time, and performing audio semantic analysis by employing audio processing and feature-based classification.
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https://aes2.org/publications/elibrary-page/?id=20327
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