Build with AssemblyAI's Speaker Diarization Model + Latest Tutorials

In June 2024, AssemblyAI updated its Speaker Diarization model to be 13% more accurate and added support for five additional languages. This improvement helps users accurately identify who is speaking in audio recordings, making it easier to analyze conversations in more languages. The Speaker Diarization feature can be applied to distinguish between speakers in audio projects and can also infer speaker names using LeMUR. It enhances audio analysis by accurately identifying and differentiating speakers, improving transcripts, enabling searchable audio, and providing better training for language-based AI tools. Additionally, AssemblyAI offers tutorials on generating subtitles with Zapier, detecting scam calls using Go with LeMUR and Twilio, content moderation on audio files with Python, building a web app to summarize YouTube reviews with LLMs, real-time speech-to-text in Java, and live speech-to-text transcription in Google Docs using Python.