Developer Builds Zero-Setup Speaker Labeling Using Pitch Measurement, No AI Model Needed

A developer building the open-source audio analysis library 'audiotrace' needed a way to label speakers in call transcripts without requiring users to set up a Hugging Face account or access token, as the popular diarization tool pyannote demands. The solution bypasses machine learning entirely by measuring the fundamental pitch frequency of each transcribed audio segment using the librosa library. Segments are then clustered into two groups — lower-pitched and higher-pitched — to distinguish between speakers such as an agent and a customer. The approach, implemented in a few dozen lines of code, works as a default fallback while still allowing users to opt into pyannote for higher accuracy when a token is available. The developer notes the method has known limitations with same-gender voices but highlights it as a practical example of preferring cheap, deterministic signal processing over heavyweight models where appropriate.