Genericize teacher reference in model card

README.md

@@ -94,7 +94,7 @@ No real Hinglish speech was used for training. The corpus was manufactured, filt
 in five steps.
 
 ### 1. Teacher
-Speech was generated by **smallest.ai Lightning V3.1**, which does native intra-sentence Hindi-English
+Speech was generated by **the teacher TTS**, which does native intra-sentence Hindi-English
 code-switching. A human verified a sample of teacher clips as natural before distillation, so the
 teacher defines the quality bar. Four Indian voices were used as the fixed voice set.
 
@@ -174,14 +174,14 @@ embedded English is recovered as English), UTMOS (naturalness), and resemblyzer
 
 - **License: non-commercial.** This is a derivative of XTTS-v2 under the Coqui Public Model License
   (CPML); it inherits CPML and is for research / non-commercial use. The training audio was
-  generated by smallest.ai; review their terms before any redistribution or commercial use.
+  generated by teacher TTS; review their terms before any redistribution or commercial use.
 - **Four fixed voices** from one teacher engine; the voices are a fairly homogeneous family.
 - **Accent is ~3% below the teacher** and sentence-initial English markers (e.g. "Wait") are
   occasionally mispronounced.
 - **Operational:** spell numbers as words (digits error out), chunk text over ~150 chars.
 - **Absolute naturalness is not human-MOS-certified;** the evidence is relative parity to a
   human-verified teacher, plus an English-biased UTMOS proxy.
-- **Single teacher:** style and artifact diversity are bounded by smallest.ai.
+- **Single teacher:** style and artifact diversity are bounded by teacher TTS.
 
 ## Provenance and intended use