Text-to-Speech
PyTorch
ONNX
Catalan
matcha-tts
acoustic modelling
speech
multispeaker
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---
language:
- ca
licence:
- apache-2.0
tags:
- matcha TTS
- speech
- text-to-speech
- catalan
pipeline_tag: text-to-speech
datasets:
- projecte-aina/festcat_trimmed_denoised
- projecte-aina/openslr-slr69-ca-trimmed-denoised
---

# Matcha TTS Catalan

## Table of Contents
<details>
<summary>Click to expand</summary>

- [Model description](#model-description)
- [Intended uses and limitations](#intended-uses-and-limitations)
- [How to use](#how-to-use)
- [Limitations and bias](#limitations-and-bias)
- [Training](#training)
- [Evaluation](#evaluation)
- [Additional information](#additional-information)

</details>

## Model description

## Intended uses and limitations

## How to use
```python
import torch
from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM

input_text = "Sovint em trobo pensant en tot allò que"

model_id  = "projecte-aina/FLOR-6.3B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
generator = pipeline(
    "text-generation",
    model=model_id,
    tokenizer=tokenizer,
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
    device_map="auto",
)
generation = generator(
    input_text,
    do_sample=True,
    top_k=10,
    eos_token_id=tokenizer.eos_token_id,
)

print(f"Result: {generation[0]['generated_text']}")
```

## Limitations and bias
At the time of submission, no measures have been taken to estimate the bias and toxicity embedded in the model. 
However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques 
on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated. 


## Training

### Adaptation


### Training data

The model was trained on 2 Catalan speech datasets

| Dataset             | Language | Hours   |
|---------------------|----------|---------|
| Festcat             | ca       | 22      |
| OpenSLR69           | ca       | 5       |

### Languages

Data comes from two different datasets: festcat and openslr69

### Framework


## Evaluation

### Results


## Additional information

### Author
The Language Technologies Unit from Barcelona Supercomputing Center.

### Contact
For further information, please send an email to <[email protected]>.

### Copyright
Copyright(c) 2023 by Language Technologies Unit, Barcelona Supercomputing Center.

### License
[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)

### Funding
This work was funded by [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).

### Disclaimer