Summary

In this chapter, we explored three key sections that delve into the comprehensive process of handling audio data. The journey began with the upload of audio data, leveraging the Whisper model for transcription, and subsequently labeling the transcriptions using OpenAI. Following this, we ventured into the creation of spectrograms and employed CNNs to label these visual representations, unraveling the intricate details of sound through advanced neural network architectures. The chapter then delved into audio labeling with augmented data, thereby enhancing the dataset for improved model training. Finally, we saw the Azure Speech service for speech to text and speech translation. This multifaceted approach equips you with a holistic understanding of audio data processing, from transcription to visual representation analysis and augmented labeling, fostering a comprehensive skill set in audio data labeling techniques.

In the next and final chapter, we will explore different...