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Kazeia Team ee186e9049 Auto-segmentation for long texts + dynamic pipeline 
- prepare_tts_native.py: auto-splits long text at sentence/comma
  boundaries, max 15 tokens per segment
- Multi-segment format: each segment gets fresh KV cache
- Formula: target_len = n_tokens × 3.2 + 5 per segment
- Tested on Edouard Baer monologue: 28 segments, 102s audio

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 		2026-04-10 00:08:59 +02:00
..
cp_et_runner.cpp Initial commit: Kazeia TTS pipeline on NPU via ExecuTorch 2026-04-09 08:42:11 +02:00
export_cp_pte.py Initial commit: Kazeia TTS pipeline on NPU via ExecuTorch 2026-04-09 08:42:11 +02:00
export_talker_pte.py Restore KV=100 + fix as-is embeds + multi-segment support 2026-04-09 22:26:20 +02:00
prepare_tts_embeds.py Add prepare_tts_embeds.py for any text + codec_sum fix 2026-04-09 14:05:42 +02:00
prepare_tts_native.py Auto-segmentation for long texts + dynamic pipeline 2026-04-10 00:08:59 +02:00
prepare_tts_segments.py Restore KV=100 + fix as-is embeds + multi-segment support 2026-04-09 22:26:20 +02:00
qc_schema_serialize_patched.py Initial commit: Kazeia TTS pipeline on NPU via ExecuTorch 2026-04-09 08:42:11 +02:00
test_cp_et_quality.py Initial commit: Kazeia TTS pipeline on NPU via ExecuTorch 2026-04-09 08:42:11 +02:00