library_name: transformers
tags:
- text-to-speech
- annotation
license: apache-2.0
language:
- en
- as
- bn
- gu
- hi
- kn
- ks
- or
- ml
- mr
- ne
- pa
- sa
- sd
- ta
- te
- ur
- om
pipeline_tag: text-to-speech
inference: false
base_model:
- ai4bharat/indic-parler-tts
HelpingAI-TTS-v1 🎤🔥
Yo, what's good! Welcome to HelpingAI-TTS-v1, your go-to for next-level Text-to-Speech (TTS) that's all about personalization, vibes, and clarity. Whether you want your text to sound cheerful, emotional, or just like you're chatting with a friend, this model's got you covered. 💯
🚀 What’s HelpingAI-TTS-v1?
HelpingAI-TTS-v1 is a beast when it comes to generating high-quality, customizable speech. It doesn’t just spit out generic text; it feels what you're saying and brings it to life with style. Add a description to your speech, like how fast or slow it should be, if it’s cheerful or serious, and BOOM — you got yourself the perfect audio output. 🎧
🛠️ How It Works: A Quick Rundown 🔥
- Transcript: The text you want to speak. Keep it casual, formal, or whatever suits your vibe.
- Caption: Describes how you want the speech to sound. Want a fast-paced, hype vibe or a calm, soothing tone? Just say it. 🔥
💡 Features You’ll Love:
- Expressive Speech: This isn’t just any TTS. You can describe the tone, speed, and vibe you want. Whether it's a peppy "Hey!" or a chill "What's up?", this model’s got your back.
- Top-Notch Quality: Super clean audio. No static. Just pure, high-quality sound that makes your words pop.
- Customizable Like Never Before: Play with emotions, tone, and even accents. It’s all about making it personal. 🌍
🔧 Get Started: Installation 🔥
Ready to vibe? Here’s how you set up HelpingAI-TTS-v1 in seconds:
pip install git+https://github.com/huggingface/parler-tts.git
🖥️ Usage: Let's Make Some Magic 🎤
Here’s the code that gets the job done. Super simple to use, just plug in your text and describe how you want it to sound. It’s like setting the mood for a movie.
import torch
from parler_tts import ParlerTTSForConditionalGeneration
from transformers import AutoTokenizer
import soundfile as sf
# Choose your device (GPU or CPU)
device = "cuda:0" if torch.cuda.is_available() else "cpu"
# Load the model and tokenizers
model = ParlerTTSForConditionalGeneration.from_pretrained("HelpingAI/HelpingAI-TTS-v1").to(device)
tokenizer = AutoTokenizer.from_pretrained("HelpingAI/HelpingAI-TTS-v1")
description_tokenizer = AutoTokenizer.from_pretrained(model.config.text_encoder._name_or_path)
# Customize your inputs: text + description
prompt = "Hey, what's up? How’s it going?"
description = "A friendly, upbeat, and casual tone with a moderate speed. Speaker sounds confident and relaxed."
# Tokenize the inputs
input_ids = description_tokenizer(description, return_tensors="pt").input_ids.to(device)
prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
# Generate the audio
generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
audio_arr = generation.cpu().numpy().squeeze()
# Save the audio to a file
sf.write("output.wav", audio_arr, model.config.sampling_rate)
This will create a super clean .wav file with the speech you asked for. 🔥
🌍 Language Support: Speak Your Language
No matter where you're from, HelpingAI-TTS-v1 has you covered. Officially supporting 20+ languages and unofficial support for a few more. That’s global vibes right there. 🌏
- Assamese
- Bengali
- Bodo
- Dogri
- Kannada
- Malayalam
- Marathi
- Sanskrit
- Nepali
- English
- Telugu
- Hindi
- Gujarati
- Konkani
- Maithili
- Manipuri
- Odia
- Santali
- Sindhi
- Tamil
- Urdu
- Chhattisgarhi
- Kashmiri
- Punjabi
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