  Building text-to-speech (TTS) synthesisers for Indian languages is a
difficult task owing to a large number of active languages. Indian languages
can be classified into a finite set of families, prominent among them,
Indo-Aryan and Dravidian. The proposed work exploits this property to build a
generic TTS system using multiple languages from the same family in an
end-to-end framework. Generic systems are quite robust as they are capable of
capturing a variety of phonotactics across languages. These systems are then
adapted to a new language in the same family using small amounts of adaptation
data. Experiments indicate that good quality TTS systems can be built using
only 7 minutes of adaptation data. An average degradation mean opinion score of
3.98 is obtained for the adapted TTSes.
  Extensive analysis of systematic interactions between languages in the
generic TTSes is carried out. x-vectors are included as speaker embedding to
synthesise text in a particular speaker's voice. An interesting observation is
that the prosody of the target speaker's voice is preserved. These results are
quite promising as they indicate the capability of generic TTSes to handle
speaker and language switching seamlessly, along with the ease of adaptation to
a new language.
