Training TTS For a New Language

[skumarlabs]

So, I want to train the TTS for an Indian language Hindi. After going through the docs, I would say I have figured out few things which are needed to achieve the above. But now I think, the more I am reading Discussions, the more I am getting confused. Can someone please help me understand what exact steps are needed to train on a new model using my dataset.

Below is what I have done based on my understanding so far:

1. I have prepared my dataset in ljspeech format so that my dataset have a metadata.csv and actual recording under wavs folder.
2. I have analyzed and cleaned my dataset as per guidlines at formatting_your_dataset
3. I have created a config.json file taking tutorial_for_nervous_beginners & faqs as reference. which is below

{
    "model": "vits",
    "batch_size": 48,
    "eval_batch_size": 16,
    "num_loader_workers": 4,
    "num_eval_loader_workers": 4,
    "run_eval": true,
    "test_delay_epochs": -1,
    "epochs": 1000,
    "text_cleaner": "basic_cleaners",
    "use_phonemes": false,
    "phoneme_language": "hi",
    "phoneme_cache_path": "phoneme_cache",
    "print_step": 25,
    "print_eval": true,
    "mixed_precision": true,
    "max_seq_len":500000,
    "output_path": "TTS/recipes/ljspeech/vits_tts",
    "test_sentences": ["मेरे प्यारे देशवासियो", "आपके परिवार के सदस्य के रूप में उपस्थित हूँ।"],
    "datasets":[{"name": "ljspeech", "meta_file_train":"metadata.csv", "path": "/path/to/dataset/root"}],
    "characters":{
        "characters": "अआइईउऊऍएऐऑओऔकखगघचछजझटठडढणतथदधनपफबभमयरलवशषसह़ािीुूृेैॉोौ्ज़ड़ढ़फ़।–‘’“”!,-.?ँंः",
        "punctuations": "-–,.:;'‘’“”()!?ँंः।",
        "phonemes": null,
        "unique": true
    },
    "audio":{
        "sample_rate": 32000
    }
 }

Now, I tried following YourTTS notebooks as well but got stuck at restoring model state dict step because of below error:
RuntimeError: Error(s) in loading state_dict for Vits: size mismatch for text_encoder.emb.weight: copying a param with shape torch.Size([165, 192]) from checkpoint, the shape in current model is torch.Size([103, 192]).

Also,

• I am not sure if I should retrain model from scratch or restore a pretrained model and finetune that since my language and it's character set is entirely different from that on which the pretrained models are available.

• Where does Speaker encoder model fits here in the process? Is it calculated automatically if I run the training with above config.json?

Can someone guide me here or point to a resource on what I need to do train a TTS on my Hindi dataset? Thanks for reading so far!

[jaggukaka]

I guess to get past the error may be you need to keep the original trained model's character set too. After that see how it goes.
Speaker encoder is a separate model.
There are two modes which you can use to have speaker specific embeddings,

1. Use a pre-trained speaker encoder and generate d_vectors for all the samples you are including in your dataset
2. Use speaker_embedding, which is another layer in the network and it learns the speaker specific embedding as you train the model.

But, probably the model which you are fine tuning is mostly trained with a speaker encoder, I guess it is better to generate d_vectors for every utterance in your data set and pass it to the model and not use speaker_embedding layer. (There are properties in config.json to set this appropriately)
You can generate d_vectors for your dataset by using this script.

Hope this information helps.

[dsunjka]

@jaggukaka I would also be very interested in your lessons learned and any hints you might have for training for a new language.

[swapnil3597]

Hi @jaggukaka, can you please share how were you able to train Telugu TTS.

[Rajashekhar-Reddy]

@swapnil3597 Have you trained Telugu TTS successfully?

[Abhi84sia]

how to apply on hindi

[nagababumo]

I guess to get past the error may be you need to keep the original trained model's character set too. After that see how it goes. Speaker encoder is a separate model. There are two modes which you can use to have speaker specific embeddings,

1. Use a pre-trained speaker encoder and generate d_vectors for all the samples you are including in your dataset
2. Use speaker_embedding, which is another layer in the network and it learns the speaker specific embedding as you train the model.

But, probably the model which you are fine tuning is mostly trained with a speaker encoder, I guess it is better to generate d_vectors for every utterance in your data set and pass it to the model and not use speaker_embedding layer. (There are properties in config.json to set this appropriately) You can generate d_vectors for your dataset by using this script.

Hope this information helps.

hii can you help me in making on hindi please, it alot to me

[erogol]

Since your character set is totally different, you might need to train from scratch but restoring from the pre-trained model would at least help the vocoder to learn faster.

[Rajashekhar-Reddy]

@jaggukaka Have you tried to train Telugu?

[souvikg544]

hello has anyone done it?

[VarunGumma]

Hi @souvikg544 @saiakarsh193 @Rajashekhar-Reddy, any update on this with YourTTS?

[sapienfrom2000s]

hey, any update on tts-hindi?

[saiakarsh193]

Hey, so I trained multiple Indian language TTS using Tacotron 2, Fast Pitch, VITS and YourTTS. The process is slightly different for each case but it is totally possible to train for a new language from scratch.

[sapienfrom2000s]

I need the VITS version for hindi and indian English if possible. Want to use piper (https://github.com/rhasspy/piper) with it.

[ianujkr]

did u trained on bengali language as well?