README.md

Examples

These examples are meant to mirror the most common pyannote-style usage patterns:

• run diarization on one WAV file
• iterate speaker turns
• compute speaker airtime
• reconcile transcript chunks with diarization output

All examples expect:

• a models directory containing segmentation-3.0.onnx, wespeaker-voxceleb-resnet34.onnx, and the PLDA .npy files
• a mono 16kHz 16-bit PCM WAV input

Populate fixtures/models with:

just download-models

Run diarization and print RTTM

cargo run --example diarize_wav -- fixtures/models fixtures/test.wav

Optional file id:

cargo run --example diarize_wav -- fixtures/models fixtures/test.wav meeting-42

Print speaker turns

This is the closest equivalent to pyannote's for turn, speaker in output.speaker_diarization usage.

cargo run --example print_turns -- fixtures/models fixtures/test.wav

Output:

start   end     speaker
4.705   46.690  SPEAKER_00
...

Compute speaker airtime

Useful for analytics, meeting summaries, or moderation dashboards.

cargo run --example speaker_airtime -- fixtures/models fixtures/test.wav

Output:

speaker     total_seconds
SPEAKER_00  341.245
...

Assign speakers to transcript chunks

This example uses an exclusive diarization view to assign one dominant speaker to each transcript chunk.

Transcript input is a tab-separated file with:

start_seconds<TAB>end_seconds<TAB>text

Example transcript:

0.000	3.200	Welcome everyone
3.200	7.800	Let's get started

Run it with:

cargo run --example assign_transcript_speakers -- fixtures/models fixtures/test.wav transcript.tsv

Output:

start   end     speaker     text
0.000   3.200   SPEAKER_00  Welcome everyone
3.200   7.800   SPEAKER_01  Let's get started