Parse Podcasts With Python: Understanding Lex Fridman’s Podcast With Deepgram ASR And Text Analysis

In this project, we analyzed several episodes of Lex Fridman’s podcast using Automatic Speech Recognition (ASR) and Natural Language Processing (NLP). We started by downloading the audio files from YouTube using youtube_dl. Then, we transcribed these audio files into text format using Deepgram's ASR API. After obtaining the transcriptions, we performed several analyses on them. Firstly, we analyzed the time spent speaking and words spoken by Lex Fridman and his guests. We found that Lex speaks for less time but says a similar number of words as his guests. Next, we used The Text API to identify common phrases mentioned in each podcast episode. This analysis revealed that Lex frequently uses adjectives such as "beautiful", "poetic", "fascinating", and "loving". We also analyzed the subjects discussed in these podcasts. Finally, we used The Text API's Named Entity Recognition (NER) feature to extract named entities from the transcribed podcasts. This helped us understand who or what was being talked about during each episode. Additionally, we generated summaries of each podcast episode using The Text API's AI text summarizer. Overall, this project demonstrated how ASR and NLP can be used together to analyze podcast transcripts effectively.