Open Source Python Text to Speech Software for Linux
Sort By:
Python Text to Speech Software for Linux
View 20 business solutionsBrowse free open source Python Text to Speech Software for Linux and projects below. Use the toggles on the left to filter open source Python Text to Speech Software for Linux by OS, license, language, programming language, and project status.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Keep company data safe with Chrome EnterpriseMake AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
-
1
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. -
2
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. -
3
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. -
4
CosyVoice
Multi-lingual large voice generation model, providing inference
CosyVoice is a multilingual large voice generation model that offers a full-stack solution for training, inference, and deployment of high-quality TTS systems. The model supports multiple languages, including Chinese, English, Japanese, Korean, and a range of Chinese dialects such as Cantonese, Sichuanese, Shanghainese, Tianjinese, and Wuhanese. It is designed for zero-shot voice cloning and cross-lingual or mix-lingual scenarios, so a single reference voice can be used to synthesize speech across languages and in code-switching contexts. 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. -
Cloud-based help desk software with ServoDeskWhat if You Could Automate 90% of Your Repetitive Tasks in Under 30 Days? At ServoDesk, we help businesses like yours automate operations with AI, allowing you to cut service times in half and increase productivity by 25% - without hiring more staff.
-
5
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. -
6
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. -
7
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. -
8
MeloTTS
High-quality multi-lingual text-to-speech library by MyShell.ai
MeloTTS is an open-source text-to-speech (TTS) system that generates natural-sounding speech from text input. It utilizes advanced machine-learning models to produce high-quality audio outputs. -
9
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. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
10
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. -
11
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. -
12
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. -
13
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. -
14
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. -
15
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). -
16
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. -
17
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. -
18
ChatTTS_colab
One-click deployment (including offline integration package)
ChatTTS_colab is a wrapper project around the ChatTTS model that focuses on “one-click” deployment, especially in Google Colab. It provides an integrated offline bundle and scripts for Windows and macOS so users can run ChatTTS locally without wrestling with complex environment setup. The repository includes Colab notebooks that launch a Gradio-based web UI and expose streaming TTS, making it possible to listen to generated audio as it is produced. A distinctive feature is the “voice gacha” system, which batch-generates many distinct voice timbres and allows users to save the ones they like into a curated voice library. It has first-class support for long-form audio generation, making it suitable for audiobooks, podcasts, or long narration tasks. The project also implements multi-speaker or role-based reading, letting users assign different voices to different characters in a script and even use a large language model to generate that script in one step. -
19
Dia
A TTS model capable of generating ultra-realistic dialogue
Dia is a neural text-to-speech model designed specifically for generating ultra-realistic dialogue in a single pass. Instead of focusing on isolated sentences or flat narration, it is optimized for conversational audio, complete with natural turn-taking, prosody, and pacing. The model can be conditioned on a reference audio sample, allowing you to control emotion, tone, and other stylistic aspects of the speech. It can also produce nonverbal vocalizations like laughter, coughs, clearing the throat, and similar sounds, which are crucial for making synthetic conversations feel human. Dia is released with pretrained checkpoints and inference code, with weights hosted on Hugging Face, so researchers and developers can quickly try it or integrate it into pipelines. The base model currently targets English and has around 1.6 billion parameters, offering a strong balance between realism and computational cost, while the ecosystem also includes Dia2. -
20
ESPnet
End-to-end speech processing toolkit
ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while still benefiting from the robust data preparation practices developed in the speech community. ESPnet provides many ready-to-run recipes for popular academic benchmarks, making it straightforward to reproduce published results or serve as baselines for new research. The toolkit also hosts numerous pretrained models and example configs, ranging from Transformer and Conformer architectures to various attention-based encoder-decoder models. -
21
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. -
22
IMS Toucan
Controllable and fast Text-to-Speech for over 7000 languages
IMS-Toucan is a toolkit for training, using, and teaching state-of-the-art text-to-speech systems, built at the Institute for Natural Language Processing (IMS), University of Stuttgart. It is the official home of ToucanTTS, a massively multilingual TTS system designed to support over 7,000 languages with a single unified framework. The toolkit focuses on being fast and controllable while not requiring huge amounts of compute, making it practical for research labs and smaller teams. It includes complete pipelines for preprocessing datasets, training models, and running inference, plus a storage configuration system to manage where models and caches are stored. IMS-Toucan ships with several ready-to-run scripts, including GUIs for interactive demos, prosody override tools, zero-shot language embedding injection, and text-to-audio file generation. Pretrained models are automatically downloaded when needed, and there is an online demo instance hosted on GPU that anyone can try. -
23
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. -
24
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. To control speaker identity, MARS5 uses a short reference audio clip, typically between 2 and 12 seconds, from which it learns the voice characteristics. It supports two main inference modes: shallow clone, which is faster and only needs the reference audio, and deep clone, which additionally uses the transcript of the reference audio to increase similarity and naturalness at the cost of more computation. -
25
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.
