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Best AI Audio Models Tools

Explore 24 AI audio models tools to find the perfect solution.

OpenVoice is a versatile instant voice cloning framework that allows users to generate speech in multiple languages using only a short audio clip from a reference speaker. The tool provides granular control over voice styles, such as emotion, accent, rhythm, pauses, and intonation, and supports zero-shot cross-lingual voice cloning, enabling users to clone voices across different languages without needing training data for those languages.

Parler-TTS

A text-to-speech inference and training library for generating high-fidelity speech from text, offering an open-source solution for TTS applications.

SpeechBrain

An all-in-one open-source conversational AI toolkit based on PyTorch offering speech recognition, text-to-speech, speaker recognition, and more.

Whisper Large

A robust speech recognition model based on a Transformer architecture that supports multilingual transcription, speech translation, and language identification.

Retrieval-based Voice Conversion WebUI

An open-source web UI that enables voice conversion using retrieval-based methods, offering configurable options and support for different models.

openai/whisper-large-v3-turbo

A finetuned, pruned version of Whisper large-v3 for automatic speech recognition and speech translation. This model reduces the number of decoding layers from 32 to 4 to achieve much faster inference, with only a minor quality trade-off. It supports 99 languages and integrates with Hugging Face Transformers for efficient transcription and translation.

OpenVoice V2

OpenVoice V2 is an advanced text-to-speech model that provides instant voice cloning with accurate tone color reproduction and flexible voice style control. It supports zero-shot cross-lingual synthesis in multiple languages and has improved audio quality over its previous version. Released under the MIT License, it is geared towards both research and commercial use.

Whisper Large v3

A state-of-the-art automatic speech recognition and translation model trained on over 5 million hours of data, capable of robust zero-shot generalization.

Whisper by OpenAI

A robust, general-purpose speech recognition model capable of multilingual transcription, translation, and language identification, built using a transformer architecture.

OpenVoice

OpenVoice is an instant voice cloning tool developed by MIT and MyShell. It offers accurate tone color cloning, flexible voice style control (including emotion, accent, rhythm, pauses, and intonation), and supports zero-shot cross-lingual voice cloning. The V2 release improves audio quality, provides native multi-lingual support (English, Spanish, French, Chinese, Japanese, Korean), and is available under the MIT License for free commercial use.

Bark

Bark is a transformer-based text-to-audio model by Suno that generates highly realistic, multilingual speech as well as music, background noise, and simple sound effects. It also produces nonverbal cues like laughing or sighing. The model is provided for research purposes with pretrained checkpoints available for inference.

CosyVoice

A multi-lingual large voice generation model which provides full-stack capabilities for inference, training, and deployment of high-fidelity voice synthesis.

GPT-SoVITS

A few-shot voice cloning and text-to-speech WebUI that can train a TTS model with just 1 minute of voice data. It supports zero-shot and few-shot TTS, cross-lingual inference, and includes integrated tools for voice separation, dataset segmentation, and ASR, making it easier to build and deploy custom TTS models.

Coqui TTS

A deep learning toolkit for advanced Text-to-Speech generation, providing pretrained models across 1100+ languages, tools for training and fine-tuning models, and utilities for dataset analysis. Battle-tested in both research and production environments.

coqui/XTTS-v2

A text-to-speech (TTS) voice generation model that enables high-quality voice cloning and cross-language speech synthesis using just a 6-second audio clip. It supports 17 languages, offers emotion and style transfer, improved speaker conditioning, and overall stability improvements over its previous version.

Dia

A text-to-speech (TTS) model capable of generating ultra-realistic dialogue in one pass, providing real-time audio generation on enterprise GPUs.

google/lyria-2

Lyria 2 is an AI music generation model by Google that produces professional-grade 48kHz stereo audio from text-based prompts. It supports various genres and implements SynthID for audio watermarking, making it suitable for direct project integration.

Minimax Speech 02 HD

A high-fidelity text-to-audio (T2A) tool that offers advanced voice synthesis, voice cloning, emotional expression, and multilingual capabilities, optimized for applications such as voiceovers and audiobooks.

Chatterbox

A state-of-the-art open source text-to-speech tool featuring imperceptible neural watermarks for secure audio generation.

Resemble Chatterbox TTS

Resemble Chatterbox is an open source, production-grade text-to-speech model by Resemble AI. It features unique emotion exaggeration control, instant voice cloning from short audio, built-in watermarking, and alignment-informed inference, making it ideal for creating expressive, natural speech for various applications.

CSM (Conversational Speech Model)

CSM is a conversational speech generation model by SesameAILabs. It generates RVQ audio codes from text and audio inputs using a Llama backbone for language processing and a specialized audio decoder to produce Mimi audio codes, enabling interactive conversational speech synthesis.

Chatterbox TTS

Chatterbox TTS is Resemble AI's first production-grade open source text-to-speech model. It offers speech generation with voice cloning and unique features such as emotion exaggeration control, alignment-informed inference, and built-in imperceptible watermarks. It is built on a 0.5B Llama backbone and benchmarked against leading closed-source systems.

OuteTTS

A new open-source text-to-speech model available in different versions (v0.2 500M and v0.3 1B) designed for efficient speech synthesis.

Bark

Bark is an open-source, transformer-based generative audio model by Suno that converts text prompts into realistic, multilingual speech as well as other audio outputs (e.g., music, background noise, and nonverbal cues). It is designed for research and commercial use, offering fast inference on both GPU and CPU.