Open Source Python Text to Speech Software
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Python Text to Speech Software
View 202 business solutionsBrowse free open source Python Text to Speech Software and projects below. Use the toggles on the left to filter open source Python Text to Speech Software by OS, license, language, programming language, and project status.
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DiffSinger
Singing Voice Synthesis via Shallow Diffusion Mechanism
DiffSinger is an open-source PyTorch implementation of a diffusion-based acoustic model for singing-voice synthesis (SVS) and also text-to-speech (TTS) in a related variant. The core idea is to view generation of a sung voice (mel-spectrogram) as a diffusion process: starting from noise, the model iteratively “denoises” while being conditioned on a music score (lyrics, pitch, musical timing). This avoids some of the typical problems of prior SVS models — like over-smoothing or unstable GAN training — and produces more realistic, expressive, and natural-sounding singing. The method introduces a “shallow diffusion” mechanism: instead of diffusing over many steps, generation begins at a shallow step determined adaptively, which leverages prior knowledge learned by a simple mel-spectrogram decoder and speeds up inference. -
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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. The tool supports around sixteen languages, including Chinese, English, Japanese, Korean, French, German, Italian, and others, and can capture reference voices directly from a microphone or from uploaded audio. -
3
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. From the CLI you can adjust parameters such as speaking rate, volume, and pitch, giving you some control over prosody without diving into SSML. The library is asynchronous under the hood, which makes it efficient for batch jobs or web services that need to synthesize many utterances concurrently. -
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OpenVoice
Instant voice cloning by MIT and MyShell. Audio foundation model
OpenVoice is a versatile instant voice cloning system that can replicate a speaker’s tone color from just a short audio clip and then generate speech in multiple languages. It is designed not only to match the timbre of the reference voice, but also to give granular control over style parameters such as emotion, accent, rhythm, pauses, and intonation. The model supports cross-lingual and even zero-shot cross-lingual voice cloning, so a speaker recorded in one language can be made to speak naturally in others. Architecturally, OpenVoice separates “tone color” cloning from style control, which makes it easier to keep a consistent identity while flexibly changing prosody or language. The project provides open-weight models, inference code, and examples, making it suitable both for research and for building production voice experiences. It is actively developed by MyShell, which also integrates OpenVoice into broader agent and entertainment workflows. -
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AI Runner
Offline inference engine for art, real-time voice conversations
AI Runner is an offline inference engine designed to run a collection of AI workloads on your own machine, including image generation for art, real-time voice conversations, LLM-powered chatbots and automated workflows. It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. At the core of its LLM stack is a mode-based architecture with specialized “modes” such as Author, Code, Research, QA and General, and a workflow manager that automatically routes user requests to the right agent based on the task. The project has a strong focus on developer ergonomics, with thorough development guidelines, environment configuration using .env variables, and a clear structure for tests, tools and agents. -
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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. The system supports zero-shot voice cloning — meaning it can mimic a target speaker’s voice from a short reference sample — making it versatile for multi-voice uses. Compared to many open-source TTS tools, IndexTTS emphasizes efficiency and controllability: it offers faster inference, simpler training pipelines, and controllable speech parameters (like duration, pitch, and prosody), which is critical for production use. -
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Chatterbox
SoTA open-source TTS
Chatterbox is Resemble AI's first production-grade open source TTS model. Licensed under MIT, Chatterbox has been benchmarked against leading closed-source systems like ElevenLabs and is consistently preferred in side-by-side evaluations. Whether you're working on memes, videos, games, or AI agents, Chatterbox brings your content to life. It's also the first open source TTS model to support emotion exaggeration control, a powerful feature that makes your voices stand out. Try it now on our Hugging Face Gradio app. If you like the model but need to scale or tune it for higher accuracy, check out our competitively priced TTS service (link). It delivers reliable performance with ultra-low latency of sub-200ms—ideal for production use in agents, applications, or interactive media. -
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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. The project is structured to be flexible through plugins and configurations so users can extend functionality without touching the core code. Applio is considered stable and mature; ongoing development is now centered on security patches, dependency maintenance, and occasional improvements, which makes it attractive for production or repeatable workflows. It also includes TensorBoard helper scripts so people training custom models can monitor metrics and experiment more systematically. -
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SoniTranslate
Synchronized Translation for Videos
SoniTranslate is a video translation and dubbing system that produces synchronized target-language audio tracks for existing video content. It provides a web UI built with Gradio, allowing users to upload a video, choose source and target languages, and then run a pipeline that handles transcription, translation and re-synthesis of speech. Under the hood, it uses advanced speech and diarization models to separate speakers, align audio with timecodes and respect subtitle timing, which lets the generated dub track stay in sync with the original video structure. The project supports a wide range of languages for translation, spanning major world languages (English, Spanish, French, German, Chinese, Arabic, etc.) and many regional or less widely spoken languages, making it suitable for broad internationalization. It offers multiple usage modes, including a Colab notebook for cloud-based experimentation, a Hugging Face Space demo for quick trials, and instructions. -
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Voice-Pro
Comprehensive Gradio WebUI for audio processing
Voice-Pro is the best gradio WebUI for transcription, translation and text-to-speech. It can be easily installed with one click. Create a virtual environment using Miniconda, running completely separate from the Windows system (fully portable). Supports real-time transcription and translation, as well as batch mode. -
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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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ebook2audiobook
Generate audiobooks from e-books, voice cloning & 1107+ languages
ebook2audiobook is a tool to convert legally obtained eBooks (non-DRM) into fully narrated audiobooks, complete with chapters and metadata. It automates the pipeline: it reads the eBook file, splits it into appropriate segments (chapters, paragraphs), uses text-to-speech (TTS) models to synthesize audio, optionally applies voice cloning, and outputs a final audiobook — ideal for people who prefer listening over reading, or for accessibility purposes. The tool supports a wide array of underlying TTS backends (XTTSv2, Bark, VITS, Fairseq, Tacotron2, YourTTS and more), which gives flexibility depending on hardware availability, voice preference, and language. It also supports a huge number of languages — apparently “+1110 languages and dialects” in its supported set — making it suitable for eBooks in many languages. -
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FastKoko
Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model
FastKoko is a self-hosted text-to-speech server built around the Kokoro-82M model and exposed through a FastAPI backend. It is designed to be easy to deploy via Docker, with separate CPU and GPU images so that users can choose between pure CPU inference and NVIDIA GPU acceleration. The project exposes an OpenAI-compatible speech endpoint, which means existing code that talks to the OpenAI audio API can often be pointed at a Kokoro-FastAPI instance with minimal changes. It supports multiple languages and voicepacks and allows phoneme based generation for more accurate pronunciation and prosody. The server also offers per-word timestamped captions, which makes it useful for creating subtitles or aligning audio with text. A built in web UI, API documentation, and debug endpoints for monitoring system status help users explore voices, test requests, and integrate the service into larger systems. -
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EPUB to Audiobook Converter
EPUB to audiobook converter, optimized for Audiobookshelf
EPUB to Audiobook Converter is a tool designed to convert EPUB ebooks into chaptered audiobooks, optimized specifically for Audiobookshelf servers. It reads each chapter from an EPUB file, generates audio using a chosen text-to-speech backend, and outputs separate MP3 files with chapter titles preserved as metadata to make navigation easier. The project supports multiple TTS providers, including Microsoft Azure TTS, EdgeTTS, OpenAI TTS, local Piper, and Kokoro via an OpenAI-compatible endpoint, allowing users to choose between cloud and self-hosted voices. A recent addition is a Gradio-based WebUI, which wraps all configuration options in a graphical interface for users who prefer not to work with the command line. The tool offers advanced options such as controlling chapter ranges, handling paragraph detection via newline modes, removing endnote markers, and using regex-based search-and-replace files to tweak pronunciations. It can be run directly with Python or via Docker. -
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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. The system is multilingual and cross-lingual, handling multiple languages in a single input without explicit phoneme markup, and is trained on large-scale datasets. -
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WhisperLive
A nearly-live implementation of OpenAI's Whisper
WhisperLive is a “nearly live” implementation of OpenAI’s Whisper model focused on real-time transcription. It runs as a server–client system in which the server hosts a Whisper backend and clients stream audio to be transcribed with very low delay. The project supports multiple inference backends, including Faster-Whisper, NVIDIA TensorRT, and OpenVINO, allowing you to target GPUs and different CPU architectures efficiently. It can handle microphone input, pre-recorded audio files, and network streams such as RTSP and HLS, making it flexible for live events, monitoring, or accessibility workflows. Configuration options let you control the number of clients, maximum connection time, and threading behavior so the server can be tuned for different deployment environments. On the client side, you can set the language, whether to translate into English, model size, voice activity detection, and output recording behavior. -
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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. The Kokoro-82M model it uses is compact (82M parameters) yet natural sounding, trained on under 100 hours of audio, and supports multiple languages, including English (US/UK), Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese. Audiblez can run entirely from the command line via a PyPI package or through a simple cross-platform GUI built on wxPython, giving both advanced users and non-technical users an accessible workflow. -
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Mocking Bird
Clone a voice in 5 seconds to generate arbitrary speech in real-time
MockingBird is an open-source voice cloning and real-time speech generation toolkit that lets you clone a speaker’s voice from a short audio sample (reportedly as little as 5 seconds) and then synthesize arbitrary speech in that voice. It builds on deep-learning based TTS / voice-cloning technology (in the lineage of projects such as Real-Time-Voice-Cloning), but extends it with support for Mandarin Chinese and multiple Chinese speech datasets — broadening its applicability beyond English. The codebase is implemented in Python (with PyTorch) and includes modules for encoder, synthesizer, vocoder, preprocessing, and inference, as well as demo scripts and a web-server interface for easier experimentation or deployment. MockingBird supports both using pretrained models and training your own synthesizer (with custom datasets), giving flexibility for voice-cloning or custom-voice synthesis depending on your needs. -
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abogen
Generate audiobooks from EPUBs, PDFs and text with captions
abogen is a tool designed to generate audiobooks (or speech narrations) from textual sources such as EPUBs, PDFs, or plain text, with synchronized captions. In other words, it automates the pipeline of reading a digital book (or document), converting its text into speech via a TTS engine, and packaging the result into an audiobook format — likely along with timestamped captions or subtitles that align with the spoken audio. This can be very useful for accessibility, content consumption on the go, or for users who prefer audio over reading. The repository supports handling common ebook formats and generating outputs that combine audio plus caption metadata. By automating text-to-speech for arbitrary documents, abogen reduces the friction of producing audiobooks and could be integrated into larger workflows (e.g., batch converting a library of texts). -
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Auto Synced & Translated Dubs
Automatically translates the text of a video based on a subtitle file
Auto-Synced-Translated-Dubs is a toolchain that automatically translates and re-dubs videos using AI voices while keeping the new speech aligned to the original timing via subtitle files. It assumes you have a human-made SRT (or similar) subtitle file; the script then uses translation services such as Google Cloud or DeepL to generate translated subtitle tracks in one or more target languages. Using the timestamps of each subtitle line, it computes the required duration of each spoken segment and synthesizes audio via neural TTS services, producing one audio clip per subtitle entry. The tool then time-stretches or compresses each TTS clip to match the original speech duration exactly, which preserves lip-sync and rhythm as closely as possible without manual editing. Finally, it combines all the clips into a single dubbed audio track that can be muxed with the original video, along with new translated subtitle files. -
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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. The SDK is designed for quick setup: after installing the package and setting an API key, you can generate speech in multiple languages and play or process the resulting audio bytes. It includes helper utilities (like play and stream) so you can either play audio locally or integrate it into your own playback or networking pipeline. -
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Luna AI
Virtual AI anchor that combines state-of-the-art technology
Luna AI is a virtual AI streamer framework designed to power an interactive VTuber that can go live on major platforms and chat with viewers in real time. It is built around a core assistant persona called “Luna AI,” which can be driven by a wide range of large language models and platforms, including GPT-style APIs, Claude, LangChain-based backends, ChatGLM, Kimi, Ollama, and many others. The project supports multiple rendering backends for the avatar, such as Live2D, Unreal Engine (UE), and “xuniren,” and can output to streaming platforms like Bilibili, Douyin, Kuaishou, WeChat Channels, Pinduoduo, Douyu, YouTube, Twitch, and TikTok. For voice, it integrates with numerous TTS engines (Edge-TTS, VITS-Fast, ElevenLabs, VALL-E-X, OpenVoice, GPT-SoVITS, Azure TTS, fish-speech, ChatTTS, CosyVoice, F5-TTS, MultiTTS, MeloTTS, and others), and can optionally pass the output through voice conversion systems like so-vits-svc or DDSP-SVC to change timbre. -
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pyttsx3
Offline Text To Speech synthesis for python
pyttsx3 is an offline text-to-speech library for Python that wraps native speech engines instead of calling cloud APIs. It is designed to work entirely without an internet connection, making it suitable for local automation, kiosks, accessibility tools, and embedded applications. On Windows it uses SAPI5, on Linux it typically uses eSpeak or eSpeak-NG, and on macOS it can use NSSpeechSynthesizer or AVSpeechSynthesizer, giving it broad cross-platform compatibility. The library exposes a simple but flexible API for controlling voice selection, speaking rate, volume, and other synthesis parameters from Python code. It supports both a high-level speak convenience function and a lower-level engine object with event hooks, queuing, and saving output to audio files. The repository includes examples and documentation that show how to adjust properties dynamically, persist synthesized output, and integrate pyttsx3 into GUIs or background services. -
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EmotiVoice
Multi-Voice and Prompt-Controlled TTS Engine
EmotiVoice is a multi-voice, prompt-controlled text-to-speech engine designed to generate highly expressive speech across thousands of voices. It supports both English and Chinese and ships with over 2,000 preset voices, making it suitable for everything from characters and virtual anchors to narration and dialogue. The core idea is prompt-based emotional and style control: you can ask the engine to speak “happy,” “sad,” “excited,” or with other high-level style prompts that shape prosody, pitch, speed, and energy. EmotiVoice provides multiple ways to interact with it, including a web interface, a Docker image, an HTTP API (including an OpenAI-compatible TTS API), and Python scripts for batch synthesis. It also supports voice cloning with your own data, backed by recipes for popular datasets like DataBaker and LJSpeech, so you can train or adapt voices to custom personas. -
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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. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management.
