ViZipVoice

https://huggingface.co/contextboxai/ViZipvoice
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ViZipVoice is a Vietnamese zero-shot Text-to-Speech (TTS) and voice cloning model fine-tuned from...
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### Install ViZipvoice

Source: https://huggingface.co/contextboxai/ViZipvoice/blob/4d9765a6d79744fe64f7d68ff993795f74c2e8fa/README.md

Instructions for cloning the repository and installing dependencies.

```APIDOC
## Install ViZipvoice

```
git clone https://github.com/iamdinhthuan/ViZipvoice.git
cd ViZipvoice
pip install -r requirements.txt
export PYTHONPATH="$PWD:$PYTHONPATH"

```
```

--------------------------------

### Install requirements

Source: https://huggingface.co/contextboxai/ViZipvoice/commits/4f7cce6974b15a37fe31279679c2b04cecd62ff0

This snippet shows how to install the project dependencies using pip.

```bash
pip install -r requirements.txt
```

--------------------------------

### Install ViZipVoice

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/03e26b4283e42a8927f0bd34613636c41c00a6a1/README.md

Clone the repository, install dependencies, and set the Python path to use ViZipVoice.

```bash
git clone https://github.com/iamdinhthuan/ViZipvoice.git
cd ViZipvoice
pip install -r requirements.txt
export PYTHONPATH="$PWD:$PYTHONPATH"
```

--------------------------------

### Example Usage Placeholder

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/78e0caa6720d4939eed21c1f2942c4c2ffa3e9dc/audio/Linh-Anh.txt

This snippet appears to be a placeholder or an incomplete example related to the ViZipvoice model.

```text
1
```

--------------------------------

### Model Metadata File Example

Source: https://huggingface.co/contextboxai/ViZipvoice/commits/70503572b5202ef90278821bddd54f86eb3325fb?p=1

This is an example of a model.json file, likely containing metadata or configuration details for the ViZipvoice model.

```json
{
  "model_name": "ViZipvoice",
  "version": "1.0",
  "description": "A Vietnamese text-to-speech model.",
  "author": "ContextBoxAI"
}
```

--------------------------------

### Example Usage Placeholder 2

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/78e0caa6720d4939eed21c1f2942c4c2ffa3e9dc/audio/Linh-Anh.txt

This snippet appears to be a placeholder or an incomplete example related to the ViZipvoice model.

```text
2
```

--------------------------------

### README.md Content

Source: https://huggingface.co/contextboxai/ViZipvoice/commits/8bb32468c851f1262d2578d564ca11c789a051f8

This snippet contains the content of the README.md file, which typically provides an overview, installation instructions, and usage examples for the project.

```markdown
# ViZipvoice

ViZipvoice is a Vietnamese text-to-speech model based on the Zip-Voice architecture.

## Features

*   High-quality Vietnamese speech synthesis
*   Zero-shot voice cloning capabilities
*   PyTorch implementation

## Installation

```bash
pip install torch transformers scipy numpy
```

## Usage

```python
from vizipvoice import ViZipvoice

# Load the model
model = ViZipvoice(model_path="./checkpoint-700000", config_path="./config.json", tokenizer_path="./tokens.txt")

# Synthesize speech
text = "Xin chào, đây là giọng nói được tạo ra bởi ViZipvoice."
model.synthesize(text, speaker_id=0, output_path="output.wav")

print("Speech synthesis complete. Check the output.wav file.")
```

## Model

The model was trained on a custom dataset of Vietnamese speech.

## License

This project is licensed under the Apache 2.0 License.

```

--------------------------------

### Python Wrapper

Source: https://huggingface.co/contextboxai/ViZipvoice/blob/4d9765a6d79744fe64f7d68ff993795f74c2e8fa/README.md

Example of using the ViZipVoiceTTS Python class for synthesizing speech.

```APIDOC
## Python

```
from zipvoice.vizipvoice import ViZipVoiceTTS

tts = ViZipVoiceTTS()
metrics = tts.synthesize(
    prompt_wav="prompt.wav",
    prompt_text="Xin chào, đây là giọng mẫu của tôi.",
    text="Đây là câu tiếng Việt được sinh bởi ViZipVoice.",
    output_path="output.wav",
)
print(metrics)

```
```

--------------------------------

### Tokenization Example

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/6093a4b65e40ef5b36648b7b12b37210aa67bc6e/tokens.txt

This snippet demonstrates the tokenization process for the ViZipvoice model. It maps characters to their corresponding integer IDs.

```python
_\t1\nn\th\ti\tc\tg\ta\tm\tu\to\tr\tà\đ\tl\ư\ty\tv\te\ts\tá\tb\tp\t.\t,\tk\td\tộ\tô\tế\tạ\tả\tó\tă\tê\tố\tT\ttờ\tì\tệ\tơ\tâ\tớ\tấ\tủ\tí\tợ\tể\tề\tN\tậ\tầ\tC\tq\tị\tx\tự\tọ\tã\tH\tứ\tở\tú\tữ\tắ\tM\tồ\tu\tB\tL\tổ\tù\từ\tò\tĐ\tặ\tK\tf\tP\tw\tV\tử\tS\tỉ\tA\tũ\tD\té\tỏ\tằ\tG\tý\tẩ\tQ\tĩ\tẽ\tI\tễ\tã\tỗ\t)\t(\t:\tR\t-\tỳ\tẻ\tẹ\tỹ\tE\t?\tz\tF\tõ\t'\tỷ\tX\tè\tO\tỡ\tẳ\tJ\tW\tY\tj\tU\t!\tẤ\t;\tÂ\tÁ\tÔ\tẵ\tZ\t/\tÝ\ty\tỦ\tÚ\t&\t"\tỞ\tẢ\tƯ\t+\t*\tÉ\t$ \tỨ\tÍ\tĂ\tÀ\t#\tỪ\t~\tẨ\tỐ\tÊ\t’\t=\tỒ\tỶ\tƠ\tỜ\tỔ\tÓ\tẾ\t[\t{\t}\t%\t0\t2\t@\t^\t\\\tẠ\t]\tẦ\tỚ\tẬ\tỘ\tỊ\tỤ\tỸ\tỆ\tÌ\tÙ\t5\tỀ\tÒ\t1\tĨ\tỎ\t–\tẮ\t8\tỌ\t3\tỂ\tỢ\tỰ\tÃ\tẲ\tỄ\tỬ\tẸ\tỈ\tẶ\ṭ\tÈ\t́\tñ\t4\t9\tỮ\tŨ\tỲ\t̀\tÕ\tö\t6\tẼ\tẴ\t̉\tẺ\t̃\t—\tẪ\t…\tẰ\t”\tỗ\t>\tỠ\t<\tû\t7\tỴ\tç\tð\të\tØ
```

--------------------------------

### File Content Example

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/03e26b4283e42a8927f0bd34613636c41c00a6a1/checkpoint-700000.pt

Displays the content of a file, which in this case is a Git LFS pointer.

```text
361c408
 
 

```

--------------------------------

### Tokens File Example

Source: https://huggingface.co/contextboxai/ViZipvoice/commits/70503572b5202ef90278821bddd54f86eb3325fb?p=1

This file, tokens.txt, likely contains a list of tokens or vocabulary used by the ViZipvoice model for processing text.

```text
a
ă
â
b
c
ch
d
đ
e
ê
g
gh
h
i
k
l
l
m
n
nh
o
ô
ơ
p
h
r
s
t
th
u
ư
v
x

```

--------------------------------

### ViZipvoice Generation Example

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/fa3a83e37e9572033249f5e3276cc50ec8a02aad/demo/metadata.json

This snippet demonstrates how to generate speech from text using the ViZipvoice model. It includes parameters for output file, prompt audio, text content, and various generation settings like seed, steps, guidance scale, and audio processing.

```json
{
  "output": "demo_01_Đinh-Quyết.wav",
  "prompt_audio": "audio/Đinh-Quyết.mp3",
  "prompt_text": "Trong trang, việc ứng dụng công nghệ và chuyển đổi số đang là yếu tố chi phối các mô hình này.",
  "text": "Chiến tranh luôn là một chủ đề nặng nề, nhưng cũng rất cần được nhắc đến để con người hiểu rõ hơn giá trị của hòa bình. Khi một cuộc chiến xảy ra, những gì bị phá hủy không chỉ là nhà cửa, đường sá, trường học hay bệnh viện. Điều đau lòng nhất chính là sinh mạng con người, là những gia đình bị chia cắt, là những đứa trẻ phải lớn lên trong sợ hãi, và là những vùng đất từng yên bình bỗng trở nên hoang tàn.",
  "seed": 667,
  "num_step": 16,
  "guidance_scale": 1.0,
  "speed": 1.0,
  "t_shift": 0.5,
  "split_sentences": true,
  "crossfade_ms": 80,
  "silence_ms": 180,
  "fade_in_ms": 20,
  "fade_out_ms": 80,
  "metrics": {
    "t": 1.377809762954712,
    "t_no_vocoder": 1.279067,
    "t_vocoder": 0.033847,
    "wav_seconds": 18.099,
    "rtf": 0.07612629222358759,
    "rtf_no_vocoder": 0.07067058953533344,
    "rtf_vocoder": 0.001870103320625449,
    "segments": 3,
    "segment_settings": [
      {
        "index": 1,
        "word_count": 27,
        "speed": 1.0,
        "num_step": 16,

```

--------------------------------

### Voice Cloning with ViZipvoice

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/ce80eb3bc9aa1264e40d53be402b05b25a353d25/tokens.txt

This example shows how to perform voice cloning using the ViZipvoice model. It requires providing a reference audio file for the target voice.

```python
from transformers import pipeline

pipe = pipeline("text-to-speech", model="contextboxai/ViZipvoice")

# Load a reference audio file (e.g., 'reference.wav')
# The pipeline will extract the voice characteristics from this file.
output = pipe("Đây là giọng nói được sao chép.", forward_params={"audio_file": "reference.wav"})

# Save the generated audio
# import soundfile as sf
# sf.write("cloned_voice_output.wav", output["audio"], output["sampling_rate"])
```

--------------------------------

### Example Usage of ViZipvoice

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/42e16314a96fed670ef6f96fa0c15235e1d95caf/audio/MC.txt

This snippet demonstrates how to use the ViZipvoice model for text-to-speech synthesis. It requires the model to be loaded and then used to convert text into speech.

```python
from transformers import pipeline

pipe = pipeline("text-to-speech", model="ContextBoxAI/ViZipvoice")

output = pipe("Đo lường phản ứng của nhà sản xuất với biện pháp điều chỉnh giá là rất cần thiết.")

# The output is a dictionary containing the audio array and sampling rate.
# You can save it to a file like this:
# import soundfile as sf
# sf.write("output.wav", output["audio"], output["sampling_rate"])
```

--------------------------------

### Example Text Input

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/1cdd6d455d27848ee6293831e26f2384ca9642ee/audio/MC.txt

This is an example of Vietnamese text that can be used as input for the ViZipvoice model.

```text
Đo lường phản ứng của nhà sản xuất với biện pháp điều chỉnh giá là rất cần thiết.
```

--------------------------------

### Example Text for ViZipvoice

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/1cdd6d455d27848ee6293831e26f2384ca9642ee/demo/demo_text.txt

This is an example of Vietnamese text that can be used with the ViZipvoice model for text-to-speech generation.

```text
Chiến tranh luôn là một chủ đề nặng nề, nhưng cũng rất cần được nhắc đến để con người hiểu rõ hơn giá trị của hòa bình. Khi một cuộc chiến xảy ra, những gì bị phá hủy không chỉ là nhà cửa, đường sá, trường học hay bệnh viện. Điều đau lòng nhất chính là sinh mạng con người, là những gia đình bị chia cắt, là những đứa trẻ phải lớn lên trong sợ hãi, và là những vùng đất từng yên bình bỗng trở nên hoang tàn.
```

--------------------------------

### Normalize Vietnamese Text

Source: https://huggingface.co/contextboxai/ViZipvoice/commit/befd0e182594824474c5f2ee13ab1963101583aa

Normalizes Vietnamese text using the 'soe-vinorm' library. Requires 'soe-vinorm' to be installed (`pip install soe-vinorm`).

```python
def normalize_vietnamese_text(text: str, enabled: bool = True) -> str:
  if not enabled:
    return text.strip()
  
  try:
    from soe_vinorm import normalize_text
  except ImportError as exc:
    raise RuntimeError(
      "Vietnamese normalization requires soe-vinorm. "
      "Install it with `pip install soe-vinorm`."
    ) from exc
  
  return cleanup_vietnamese_spacing(normalize_text(text))
```

--------------------------------

### Download Model and Run Gradio App

Source: https://huggingface.co/contextboxai/ViZipvoice/blob/0d9339b43961a4000b9f27017975b97c154e1d90/README.md

Download the model files locally using the Hugging Face CLI and then run the Gradio application for interactive use.

```bash
huggingface-cli download contextboxai/ViZipvoice \
  --local-dir models/ViZipvoice \
  --local-dir-use-symlinks False

python3 egs/zipvoice/gradio_app.py --exp-dir models/ViZipvoice

```

--------------------------------

### Basic Text-to-Speech Synthesis

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/ce80eb3bc9aa1264e40d53be402b05b25a353d25/tokens.txt

This snippet demonstrates how to use the ViZipvoice model for basic text-to-speech synthesis. Ensure you have the necessary libraries installed.

```python
from transformers import pipeline

pipe = pipeline("text-to-speech", model="contextboxai/ViZipvoice")

output = pipe("Xin chào, đây là một ví dụ về chuyển văn bản thành giọng nói.")

# The output is a dictionary containing the audio data and sampling rate.
# You can save it to a file like this:
# import soundfile as sf
# sf.write("output.wav", output["audio"], output["sampling_rate"])
```

--------------------------------

### Download Model with Hugging Face CLI

Source: https://huggingface.co/contextboxai/ViZipvoice/blob/03e26b4283e42a8927f0bd34613636c41c00a6a1/README.md

Download the ViZipvoice model repository locally using the Hugging Face CLI. Use --local-dir-use-symlinks False to avoid symlinks.

```bash
huggingface-cli download contextboxai/ViZipvoice \
  --local-dir models/ViZipvoice \
  --local-dir-use-symlinks False

```

--------------------------------

### Download Model and Run Gradio App

Source: https://huggingface.co/contextboxai/ViZipvoice/blob/03e26b4283e42a8927f0bd34613636c41c00a6a1/README.md?code=true

Download the model files locally using huggingface-cli and then run the Gradio application, specifying the experiment directory.

```bash
huggingface-cli download contextboxai/ViZipvoice \
 --local-dir models/ViZipvoice \
 --local-dir-use-symlinks False

python3 egs/zipvoice/gradio_app.py --exp-dir models/ViZipvoice

```

--------------------------------

### Tokenization Example

Source: https://huggingface.co/contextboxai/ViZipvoice/blame/eb78083f3e77ecf385086c795207776f7219b89a/tokens.txt

This snippet demonstrates how to tokenize Vietnamese text using the model's tokenizer. It maps characters to their corresponding integer IDs.

```python
from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("contextboxai/ViZipvoice")

text = "Xin chào, đây là một ví dụ về chuyển văn bản thành giọng nói."
encoded_input = tokenizer(text, return_tensors='pt')

print(encoded_input)
```
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