Search Results for "python user interface"
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Showing 12 open source projects for "python user interface"
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1
Fish Audio Python SDK
The official Python library for the Fish Audio API
...The SDK is useful for developers building voice products, prototypes, assistants, content tools, or automated audio pipelines. Its main value is simplifying integration with Fish Audio services through a clean Python interface. -
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kokoro-onnx
TTS with kokoro and onnx runtime
kokoro-onnx is a text-to-speech toolkit that wraps the Kokoro neural TTS model in an easy-to-use ONNX Runtime interface, so you can generate speech from Python with minimal setup. It focuses on running efficiently on commodity hardware, including macOS with Apple Silicon, while still delivering near real-time performance for many use cases. The project ships prebuilt model files and a simple example script, so you can go from installation to producing an audio.wav file in just a few steps. ... -
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OuteTTS
Interface for OuteTTS models
...The project supports multiple backends including llama.cpp (Python bindings and server), Hugging Face Transformers, ExLlamaV2, VLLM and a JavaScript interface via Transformers.js, allowing it to run on CPUs, NVIDIA CUDA GPUs, AMD ROCm, Vulkan-capable GPUs, and Apple Metal. 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. -
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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. ... -
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gTTS
Python library and CLI tool to interface with Google Translate
gTTS (Google Text-to-Speech) is a Python library and command-line tool that wraps the speech functionality of Google Translate. It lets you send text to the Google Translate TTS endpoint and receive spoken audio back as MP3 data, either written to a file, a file-like object, or standard output. The library is designed to handle long texts, using a speech-specific sentence tokenizer that keeps intonation and punctuation natural while splitting requests into acceptable chunks. It supports... -
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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. ... -
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... -
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Speech-AI-Forge
Speech-AI-Forge is a project developed around TTS generation model
Speech-AI-Forge is a full-stack project built around modern text-to-speech generation models, providing both an API server and a Gradio-based web UI for interactive use. At its core, it acts as a hub that wires together multiple speech-related capabilities, including TTS, speech-to-text and LLM-based control flows, behind a consistent interface. The system is designed to be deployed in several ways: you can try it online via hosted demos, spin it up in a one-click Colab environment, run it... -
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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... -
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TITTSE
Two Integrated Text To Speech Engines uses MMS & Silero
TITTSE is a Python Application that allows you to easily and quickly convert text to speech in 15 different languages (or add more easily) using Two TTS Engines. All you need is a text file ending in the tittse extension with 4 header lines including the TITTSE language code (see documentation for your language), the 'base' file name for the audio files TITTSE creates, voice gender (girl or boy), offset (file numbers added to base file name start at this number). After those first four... -
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StoryTeller
Multimodal AI Story Teller, built with Stable Diffusion, GPT, etc.
...The final video will be saved as /out/out.mp4, alongside other intermediate images, audio files, and subtitles. For more advanced use cases, you can also directly interface with Story Teller in Python code. -
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Dia-1.6B
Dia-1.6B generates lifelike English dialogue and vocal expressions
...It is optimized for English and built for real-time performance on enterprise GPUs, though CPU and quantized versions are planned. The format supports [S1]/[S2] tags to differentiate speakers and integrates easily into Python workflows. While not tuned to a specific voice, user-provided audio can guide output style. Licensed under Apache 2.0, Dia is intended for research and educational use, with explicit restrictions on misuse like identity mimicry or deceptive content.
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