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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - audio-classification
+  - text-to-speech
+language:
+  - en
+  - hi
+  - te
+  - ta
+size_categories:
+  - 1K<n<10K
+tags:
+  - speaker-encoding
+  - cross-lingual
+  - code-switching
+  - indic
+  - synthetic
+---
+
+# Codeswitch Pairs LASE — Indian-accent held-out corpus
+
+1369 held-out cross-script utterance pairs from 8 ElevenLabs Indian-English Multilingual voices. Surfaces the accent-conditional finding: off-the-shelf encoders cluster Indian-accent voices closely regardless of script, while Western voices show large script-conditional gaps.
+
+Each row is one synthesized utterance with metadata; pairs are reconstructed at evaluation time by joining on `voice_id` (same voice, different script = cross-script pair).
+
+## Schema (manifest.jsonl)
+
+```json
+{
+  "voice_id": "21m00Tcm4TlvDq8ikWAM",
+  "lang": "en | hi | te | ta",
+  "text": "the prompt text",
+  "wav_path": "<voice_name>/<lang>_NNN.wav",
+  "quality": {"cosine": 0.97, "utmos": 4.6}
+}
+```
+
+Audio is 16 kHz mono WAV, ~2 s/utterance.
+
+## Stats
+
+- **Pairs**: 1369
+- **Voices**: 8
+- **Languages**: en, hi, te, ta
+- **Quality gate**: WavLM-cosine ≥ 0.90 vs the voice's reference clip
+
+## Provenance
+
+Synthesized using the [ElevenLabs Multilingual v2](https://elevenlabs.io) API. Voice IDs are public ElevenLabs catalog voices used under their TOS for research/evaluation purposes. Text prompts are short generic English phrases translated/transliterated into each target script.
+
+## Companion paper
+
+LASE: Language-Adversarial Speaker Encoding for Indic Cross-Script Identity Preservation (arXiv:TBD)
+
+## License
+
+CC-BY-4.0.

multi_encoder_secs.json

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+  }
+}