Praha-Labs/RIMA-TTS-v1

RIMA-TTS v1

RIMA-TTS v1 is a multilingual Indic LoRA adapter for Chatterbox TTS.

This is not a standalone merged model. It is a PEFT/LoRA adapter that must be used with the Chatterbox TTS base model and the included Indic tokenizer.

Recommended Adapter

Recommended checkpoint: adapters/checkpoint-12000.

The final adapter is also included at adapters/final, but checkpoint 12000 is recommended based on listening tests.

Supported Languages

Code	Language
hi	Hindi
ta	Tamil
te	Telugu
ml	Malayalam
kn	Kannada
bn	Bengali
mr	Marathi
gu	Gujarati
pa	Punjabi
ur	Urdu
or	Odia
as	Assamese

Included Adapters

• adapters/checkpoint-8000
• adapters/checkpoint-9000
• adapters/checkpoint-10000
• adapters/checkpoint-11000
• adapters/checkpoint-12000
• adapters/checkpoint-12068
• adapters/final

Each adapter folder contains adapter_config.json and adapter_model.safetensors.

Training Data

• Dataset: ai4bharat/Rasa
• Languages: 12 Indic languages
• Target duration: 20 hours per language
• Total target duration: about 240 hours
• Training rows: 144,812

Training Configuration

Setting	Value
Base model	Chatterbox TTS
Training type	LoRA adapter finetune
Epochs	2
Steps	12,068
Batch size	24
Gradient accumulation	1
Learning rate	6e-5
LoRA rank	128
LoRA alpha	256
Tokenizer vocab size	3,358
Trainable params	97,480,704
Total params	635,321,344
Trainable %	15.34%

Training Result

Metric	Value
Final train loss	4.0169
Final logged loss	4.5739
Runtime	5h 33m 44s
Samples/sec	14.463
Steps/sec	0.603

Evaluation

Fixed multilingual eval samples were generated every 1000 steps across all 12 languages.

Manual listening tests showed strong early performance by checkpoint 2000 for Hindi, Tamil, and Malayalam. Checkpoint 12000 is currently recommended after later listening comparison.

Files

• tokenizer/tokenizer_indic_12lang.json
• configs/strong_run_config.py
• configs/train_multilingual.py
• training/strong_run_train.log
• training/dataset_summary.json

Usage Notes

This adapter requires:

1. Chatterbox TTS base model files
2. tokenizer/tokenizer_indic_12lang.json
3. One adapter folder from adapters/

Use adapters/checkpoint-12000 unless comparing checkpoints.

Limitations

• This is an adapter only, not a full merged model.
• Quality may vary by language.
• Voice cloning quality depends on the reference audio.
• Formal benchmark metrics such as MOS, WER, CER, or speaker similarity are not included yet.
• Evaluate carefully before production use.

Attribution

• Base model: Chatterbox TTS
• Training data: ai4bharat/Rasa
• Finetuning: RIMA-TTS v1 multilingual Indic adapter