Search Results for "quality"
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Showing 40 open source projects for "quality"
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Applio
A simple, high-quality voice conversion tool focused on ease of use
Applio is a high-quality voice conversion toolkit designed to make modern RVC/VITS-based voice cloning accessible to non-experts. It focuses strongly on ease of use: installation scripts for Windows, Linux, and macOS set up dependencies and then launch a browser-based Gradio interface. Within that interface, users can train and run voice conversion models for tasks like singing conversion, speech-to-speech transformation, and voice cloning. -
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IndexTTS2
Industrial-level controllable zero-shot text-to-speech system
IndexTTS is a modern, zero-shot text-to-speech (TTS) system engineered to deliver high-quality, natural-sounding speech synthesis with few requirements and strong voice-cloning capabilities. It builds on state-of-the-art models such as XTTS and other modern neural TTS backbones, improving them with a conformer-based speech conditional encoder and upgrading the decoder to a high-quality vocoder (BigVGAN2), leading to clearer and more natural audio output. -
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Kitten TTS
State-of-the-art TTS model under 25MB
KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis. -
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LuxTTS
A high-quality rapid TTS voice cloning model
LuxTTS is an open-source text-to-speech (TTS) system focused on delivering high-quality, rapid voice synthesis and voice cloning that runs extremely fast and efficiently on consumer hardware. It implements a lightweight architecture based on ZipVoice and optimized sampling techniques so that it can generate speech at speeds up to roughly 150 times real-time on a single GPU and faster than real-time on CPU, all while producing audio at high fidelity with 48 kHz quality. ... -
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VoxCPM2
Tokenizer-Free TTS for Multilingual Speech Generation
VoxCPM2 is an advanced open-source text-to-speech system that redefines speech synthesis by eliminating traditional tokenization and instead generating continuous speech representations through a diffusion-based autoregressive architecture. Built on top of the MiniCPM model family, it enables highly natural, expressive, and context-aware speech generation that adapts tone, emotion, and pacing directly from input text. The system is trained on massive multilingual datasets, enabling support... -
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OmniVoice
High-Quality Voice Cloning TTS for 600+ Languages
The OmniVoice project is a cutting-edge multilingual text-to-speech system designed to generate high-quality speech across more than 600 languages. Built on a diffusion language model-style architecture, it combines scalability with strong performance, enabling both natural-sounding voice synthesis and efficient inference speeds. One of its most notable capabilities is zero-shot voice cloning, allowing users to replicate a speaker’s voice using only a short reference audio clip. ... -
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kokoro-onnx
TTS with kokoro and onnx runtime
...The package is distributed on PyPI, meaning you can integrate it directly into applications or scripts using standard Python tooling. It also recommends pairing with an external G2P package to improve pronunciation quality, especially for more complex languages or names, and is licensed under permissive MIT and Apache-style licenses. -
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Matcha-TTS
A fast TTS architecture with conditional flow matching
Matcha-TTS is a non-autoregressive neural text-to-speech architecture that uses conditional flow matching to generate speech quickly while maintaining natural quality. It models speech as an ODE-based generative process, and conditional flow matching lets it reach high-quality audio in only a few synthesis steps, which greatly reduces latency compared to score-matching diffusion approaches. The model is fully probabilistic, so it can generate diverse realizations of the same text while still sounding stable and intelligible. ... -
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Qwen3-TTS
Qwen3-TTS is an open-source series of TTS models
Qwen3-TTS is an open-source text-to-speech (TTS) project built around the Qwen3 large language model family, focused on generating high-quality, natural-sounding speech from plain text input. It provides researchers and developers with tools to transform text into expressive, intelligible audio, supporting multiple languages and voice characteristics tuned for clarity and fluidity. The project includes pre-trained models and inference scripts that let users synthesize speech locally or integrate TTS into larger pipelines such as voice assistants, accessibility tools, or multimedia generation workflows. ... -
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VibeVoice ComfyUI
ComfyUI integration for Microsoft's VibeVoice text-to-speech model
...It exposes VibeVoice as a set of custom nodes so you can build single-speaker and multi-speaker voice generation pipelines visually, combining TTS with other audio or generative components. The integration supports high-quality single-speaker synthesis as well as scripted multi-speaker conversations, with optional voice cloning from audio samples for each speaker. It includes advanced control over generation parameters like attention backend, diffusion steps, sampling temperature, guidance scale, and quantization settings, allowing users to tune the trade-offs between quality, VRAM usage, and speed. ... -
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CosyVoice
Multi-lingual large voice generation model, providing inference
...CosyVoice 2.0 significantly improves on version 1.0 by boosting accuracy, stability, speed, and overall speech quality, making it more suitable for production environments. The repository contains training recipes, inference pipelines, deployment scripts, and integration examples, positioning it as a comprehensive toolkit rather than just a set of model weights. -
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Miso TTS
Miso TTS is an 8 billion, highly emotive text-to-speech model
Miso TTS is an advanced 8-billion-parameter text-to-speech model developed by Miso Labs for generating highly expressive and natural-sounding conversational speech. Built on an RVQ Transformer architecture inspired by Sesame CSM, it combines a powerful Llama-based backbone with an autoregressive audio decoder to produce high-quality audio from text. The model supports both standard speech synthesis and voice-conditioned generation using optional audio prompts for voice cloning. Miso TTS generates Mimi audio codes and can leverage conversation history to create more contextually aware and realistic dialogue. Designed for local deployment, it offers watermarking by default to help promote responsible use of generated audio. ... -
13
ElevenLabs Python
The official Python SDK for the ElevenLabs API
elevenlabs-python is the official Python SDK for the ElevenLabs API, giving developers a convenient way to access ElevenLabs’ high-quality, lifelike voices. The library wraps the HTTP API into a typed Python client, so you can perform text-to-speech, streaming, voice cloning, voice management, and agents-related operations with simple method calls. It exposes ElevenLabs’ main models such as Eleven Multilingual v2, Eleven Flash v2.5, and Eleven Turbo v2.5, each targeting different trade-offs between latency, cost, and quality. ... -
14
edge-tts
Use Microsoft Edge's online text-to-speech service from Python
edge-tts is a Python module and command-line tool that gives you direct access to Microsoft Edge’s online text-to-speech service without needing the Edge browser, Windows, or any API key. It wraps the same cloud voices used by Edge, exposing them through a simple CLI (edge-tts, edge-playback) and a Python API, so you can script high-quality speech generation in your own applications. The tool lets you list available voices, specify locale and voice name, and generate audio files in common formats like MP3 or WAV. It also supports generating subtitle files (such as SRT or VTT) alongside the speech, which is handy for video narration, e-learning, or accessibility workflows. ... -
15
Fish Speech
SOTA Open Source TTS
Fish Speech is a state-of-the-art open-source text-to-speech project that has evolved into the OpenAudio series of advanced TTS models. The repository hosts the code and tooling for training, fine-tuning, and serving high-quality TTS, while the current flagship models (OpenAudio-S1 and S1-mini) are distributed via Fish Audio’s playground and Hugging Face. The models are evaluated with Seed TTS metrics and achieve exceptionally low word and character error rates, indicating strong intelligibility and alignment between text and audio. Fish Speech emphasizes expressive and controllable voices: it supports a long list of emotion tags, tone markers, and special audio effect markers that can be embedded in the text to drive prosody and vocal style, from basic emotions to nuanced states like sarcastic, conciliative, or hysterical. ... -
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Audiblez
Generate audiobooks from e-books
Audiblez is a tool for generating high-quality .m4b audiobooks directly from .epub e-books using the Kokoro-82M neural text-to-speech model. It focuses on making audiobook creation easy and fast: from a single command, the tool splits an e-book into chapters, synthesizes audio for each section, and then merges the results into a structured audiobook with chapter-based WAV files and a final .m4b container. -
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GLM-TTS
Controllable & emotion-expressive zero-shot TTS
GLM-TTS is an advanced text-to-speech synthesis system built on large language model technologies that focuses on producing high-quality, expressive, and controllable spoken output, including features like emotion modulation and zero-shot voice cloning. It uses a two-stage architecture where a generative LLM first converts text into intermediate speech token sequences and then a Flow-based neural model converts those tokens into natural audio waveforms, enabling rich prosody and voice character even for unseen speakers. ... -
18
MARS5
MARS5 speech model (TTS) from CAMB.AI
MARS5-TTS is CAMB.AI’s open-source English speech model designed for high-quality text-to-speech and voice emulation. It uses a two-stage architecture that combines an autoregressive (AR) model with a non-autoregressive (NAR) model, giving it both expressiveness and speed. The model is built to handle prosodically challenging content such as sports commentary, anime dialogue, and other high-energy or highly varied speech patterns with realistic rhythm and intonation. -
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clone-voice
A sound cloning tool with a web interface, using your voice
Clone-voice is a local voice-cloning tool that lets you synthesize speech in any target voice or convert one recording into another voice using the same timbre. It is built around Coqui’s XTTS-v2 model, so it inherits multilingual support and modern neural TTS quality while wrapping it in a user-friendly desktop workflow. The app is designed to be very easy to use: you download a precompiled package, double-click app.exe, and it launches a browser-based web interface where you control cloning and synthesis. It does not require an NVIDIA GPU to run basic tasks, although GPU acceleration can be used when available, making it accessible on modest machines. ... -
20
MLX-Audio
A text-to-speech, speech-to-text and speech-to-speech library
MLX-Audio is a speech library built on Apple’s MLX framework and optimized for Apple Silicon machines (M-series Macs). It focuses on text-to-speech and speech-to-speech workflows, with APIs and a command-line interface that make it easy to generate high-quality audio from text. Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. ... -
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RealtimeTTS
Converts text to speech in realtime
...The library is engine-agnostic and plugs into a wide range of cloud and local TTS systems, including OpenAI, ElevenLabs, Azure, Coqui, Piper, StyleTTS2, Edge TTS, Google TTS, system TTS and others, so you can swap providers without rewriting your pipeline. It supports both internet-based engines and fully local engines, which lets you choose between privacy, cost, and quality trade-offs. RealtimeTTS also includes robustness features such as automatic fallbacks when a backend fails, so production systems can stay responsive even if one TTS provider is temporarily unavailable. -
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OpenAI-Compatible Edge-TTS API
Free, high-quality text-to-speech API endpoint to replace OpenAI
OpenAI-Compatible Edge-TTS API is a local, OpenAI-compatible text-to-speech API that uses edge-tts—Microsoft Edge’s online TTS service—as the backend. The project emulates the /v1/audio/speech endpoint used by OpenAI, so any client that can talk to the OpenAI TTS API can be redirected to this service with minimal changes. It exposes parameters for input text, voice selection, audio format, and playback speed, mirroring the OpenAI interface while mapping popular OpenAI voice names to... -
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FireRedTTS-2
Long-form streaming TTS system for multi-speaker dialogue generation
FireRedTTS2 is a next-generation open-source text-to-speech (TTS) system focused on long-form, streaming speech synthesis for multi-speaker dialogue, delivering stable natural speech with context-aware prosody and reliable speaker transitions that support real-time and conversational applications. It features a specialized streaming speech tokenizer and a dual-transformer architecture that enables low latency and high-quality synthesis, making it suitable for interactive systems like chatbots, podcasts, and applications where dynamic turn-taking between speakers is essential. FireRedTTS2 supports multilingual output and speaker flexibility, enabling scenarios that involve language switching, cross-lingual voice cloning, and expressive dialogue generation that maintains consistency over longer utterances. -
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WavTokenizer
SOTA discrete acoustic codec models with 40/75 tokens per second
WavTokenizer is a state-of-the-art discrete acoustic codec designed specifically for audio language modeling, capable of compressing 24 kHz audio into just 40 or 75 tokens per second while preserving high perceptual quality. It is built to represent speech, music, and general audio with extremely low bitrate, making it ideal as a front-end for large audio language models like GPT-4o and similar architectures. The model uses a single-quantizer design together with temporal compression to achieve extreme compression without sacrificing reconstruction fidelity. ... -
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OuteTTS
Interface for OuteTTS models
...It also includes a notion of speaker profiles: you can create a speaker from a short audio sample, save it as JSON, and reuse it for consistent voice identity across generations and sessions. For best quality, the model is designed to work with a reference speaker clip and will inherit emotion, style, and accent from that reference.