Showing 20 open source projects for "input-output model"

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  • 1
    Dia2

    Dia2

    TTS model capable of streaming conversational audio in realtime

    Dia2 is a streaming dialogue text-to-speech model created by Nari Labs for generating conversational audio in real time. It is designed to begin producing speech before receiving the entire input text, which makes it useful for interactive voice applications. The model supports audio conditioning, allowing generated speech to follow a reference voice or conversational style more naturally.
    Downloads: 0 This Week
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  • 2
    GLM-4-Voice

    GLM-4-Voice

    GLM-4-Voice | End-to-End Chinese-English Conversational Model

    GLM-4-Voice is an open-source speech-enabled model from ZhipuAI, extending the GLM-4 family into the audio domain. It integrates advanced voice recognition and generation with the multimodal reasoning capabilities of GLM-4, enabling smooth natural interaction via spoken input and output. The model supports real-time speech-to-text transcription, spoken dialogue understanding, and text-to-speech synthesis, making it suitable for conversational AI, virtual assistants, and accessibility applications. ...
    Downloads: 1 This Week
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  • 3
    WhisperLive

    WhisperLive

    A nearly-live implementation of OpenAI's Whisper

    ...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.
    Downloads: 44 This Week
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  • 4
    Step-Audio

    Step-Audio

    Open-source framework for intelligent speech interaction

    Step-Audio is a unified, open-source framework aimed at building intelligent speech systems that combine both comprehension and generation: it integrates large language models (LLMs) with speech input/output to handle not only semantic understanding but also rich vocal characteristics like tone, style, dialect, emotion, and prosody. The design moves beyond traditional separate-component pipelines (ASR → text model → TTS), instead offering a multimodal model that ingests speech or audio and produces speech accordingly, enabling natural dialogue, voice cloning, and expressive speech synthesis. ...
    Downloads: 0 This Week
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  • 5
    VoxCPM2

    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 for dozens of languages and dialects while maintaining high fidelity and realism in generated audio. VoxCPM stands out for its ability to perform voice cloning with minimal input, capturing not only the speaker’s timbre but also nuanced features such as rhythm, accent, and emotional delivery. ...
    Downloads: 19 This Week
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  • 6
    GLM-TTS

    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. ...
    Downloads: 0 This Week
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  • 7
    Qwen3-TTS

    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. ...
    Downloads: 12 This Week
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  • 8
    MetaVoice-1B

    MetaVoice-1B

    Foundational model for human-like, expressive TTS

    MetaVoice — in the form of its source repository “metavoice-src” — is a large-scale text-to-speech (TTS) model. Specifically, the base model (MetaVoice-1B) uses around 1.2 billion parameters and has been trained on a massive dataset — reportedly around 100,000 hours of speech data. The goal is to provide human-like, expressive, and flexible TTS: able to generate natural-sounding speech that can handle diverse inputs and likely generalize over voice styles, intonation, prosody, and perhaps...
    Downloads: 1 This Week
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  • 9
    RealtimeTTS

    RealtimeTTS

    Converts text to speech in realtime

    RealtimeTTS is a low-latency text-to-speech library built for real-time applications such as voice chat with LLMs, assistants, and interactive tools. It is designed around a streaming model: you can feed it text incrementally (for example, as an LLM responds) and get audio output almost immediately, which keeps end-to-end latency very low. 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. ...
    Downloads: 2 This Week
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  • 10
    Audiblez

    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...
    Downloads: 22 This Week
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  • 11
    MOSS-TTS-Nano

    MOSS-TTS-Nano

    MOSS-TTS-Nano is an open-source multilingual tiny speech generation

    MOSS-TTS-Nano is a lightweight text-to-speech model designed for real-time voice generation in resource-constrained environments. It is part of the broader MOSS-TTS family and focuses on delivering high-quality speech synthesis with a compact architecture. The model operates efficiently on CPU-only systems, enabling deployment without specialized hardware. It supports multilingual voice cloning and produces high-fidelity audio with low latency. The system uses an autoregressive audio...
    Downloads: 0 This Week
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  • 12
    MLX-Audio

    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...
    Downloads: 6 This Week
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  • 13
    gTTS

    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 customizable text pre-processors, which can correct pronunciations, tweak formatting, or handle domain-specific vocabulary before sending it to the API. gTTS is primarily aimed at developers who want a quick way to add cloud-backed speech to scripts, apps, or pipelines without managing any model weights locally. ...
    Downloads: 5 This Week
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  • 14
    OmniVoice

    OmniVoice

    High-Quality Voice Cloning TTS for 600+ Languages

    ...The system also includes advanced features like non-verbal expression tags and pronunciation overrides, enabling expressive and precise output. With support for both API-based and command-line usage, it is designed for research, production, and experimentation alike.
    Downloads: 38 This Week
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  • 15
    Miso TTS

    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...
    Downloads: 0 This Week
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  • 16
    MARS5

    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...
    Downloads: 0 This Week
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  • 17
    Qwen2.5-Omni

    Qwen2.5-Omni

    Capable of understanding text, audio, vision, video

    Qwen2.5-Omni is an end-to-end multimodal flagship model in the Qwen series by Alibaba Cloud, designed to process multiple modalities (text, images, audio, video) and generate responses both as text and natural speech in streaming real-time. It supports “Thinker-Talker” architecture, and introduces innovations for aligning modalities over time (for example synchronizing video/audio), robust speech generation, and low-VRAM/quantized versions to make usage more accessible. It holds...
    Downloads: 0 This Week
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  • 18
    ChatTTS_colab

    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”...
    Downloads: 1 This Week
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  • 19
    VALL-E X

    VALL-E X

    Open source implementation of Microsoft's VALL-E X zero-shot TTS model

    VALL-E-X is an open-source implementation of Microsoft’s VALL-E X zero-shot text-to-speech model, focused on multilingual, cross-lingual voice cloning. It is capable of synthesizing speech in English, Chinese, and Japanese from text while mimicking the voice characteristics of a speaker given only a short 3–10 second prompt. The model attempts to match not just timbre, but also tone, pitch, emotion, and prosody of the reference audio, resulting in highly personalized output. ...
    Downloads: 0 This Week
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  • 20
    Dia-1.6B

    Dia-1.6B

    Dia-1.6B generates lifelike English dialogue and vocal expressions

    Dia-1.6B is a 1.6 billion parameter text-to-speech model by Nari Labs that generates high-fidelity dialogue directly from transcripts. Designed for realistic vocal performance, Dia supports expressive features like emotion, tone control, and non-verbal cues such as laughter, coughing, or sighs. The model accepts speaker conditioning through audio prompts, allowing limited voice cloning and speaker consistency across generations.
    Downloads: 0 This Week
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