30 open-source projects similar to open-mmlab/amphion, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Amphion alternative.
Audiocraft is a deep learning audio library and machine learning framework designed for training, fine-tuning, and evaluating generative models for music and sound effects. It functions as a text-to-music generative model and a neural audio codec, providing the tools necessary to compress audio signals into discrete representations and synthesize high-fidelity waveforms from textual descriptions. The framework is distinguished by its ability to combine multiple conditioning signals, allowing for the generation of audio based on text prompts, melodic excerpts, or style-based audio clips. It al
This project is a deep learning text-to-speech toolkit used for training and deploying neural speech synthesis models. It provides a comprehensive framework for converting written text into spoken audio, utilizing neural vocoders to transform synthesized spectrograms into high-fidelity audio waveforms. The toolkit includes a voice cloning system that replicates specific human voices by extracting speaker embeddings from short audio samples. It also supports multi-speaker audio synthesis, allowing the generation of speech across different vocal identities using specialized model architectures.
ESPnet is a comprehensive speech processing toolkit and PyTorch-based trainer designed for building end-to-end speech recognition, synthesis, and translation models. It provides a structured framework for developing automatic speech recognition systems using transducer and encoder-decoder architectures, alongside engines for text-to-speech synthesis and speech translation pipelines. The project distinguishes itself through a recipe-based workflow execution system that ensures experimental reproducibility by running standardized sequences of scripts for data preparation and model training. It
Qwen3-TTS is a large language model text-to-speech engine designed to convert written text into natural-sounding human speech. It functions as an audio tokenizer and a generative system for speech synthesis. The project features a promptable voice designer for creating synthetic vocal personas based on natural language descriptions. It also includes a zero-shot voice cloning tool that mimics a target speaker using a short reference audio clip and a transcript. The system provides a framework for speech model fine-tuning to improve speaker likeness and quality through supervised training. Add
Magenta is a comprehensive toolkit for training, synthesizing, and performing music through neural models and hardware-integrated engines. It functions as a machine learning framework that enables the generation, manipulation, and real-time performance of audio, providing the structural foundations for musical intelligence through hierarchical sequence modeling and symbolic processing. The project distinguishes itself by enabling real-time, low-latency neural audio synthesis that can be integrated directly into professional digital audio workstations. It supports interactive musical jamming a
Tortoise-tts is a neural text-to-speech engine and voice cloning toolkit designed for high-quality audio generation. It functions as a zero-shot synthesis system, meaning it can generate speech for unseen speakers without requiring additional training or fine-tuning for each new voice. The system specializes in replicating human vocal characteristics using small sets of reference audio clips. It allows for the extraction of voice latents to mimic specific speakers, the generation of random synthetic identities, and the blending of multiple voice profiles to create hybrid vocal identities. Th
MegaTTS3 is a bilingual speech synthesis system that generates natural-sounding speech in Chinese and English, including seamless code-switching within a single utterance. It functions as a text-to-speech engine, voice cloning system, and speech-to-text alignment tool, built around an acoustic latent compression model that encodes high-resolution audio into compact representations for efficient processing. The system distinguishes itself through accent intensity control, allowing adjustment of a speaker's accent strength in generated speech, and voice cloning from short audio samples for pers
TensorFlowTTS is a neural speech synthesis framework used to convert text into high-fidelity audio waveforms. It provides a toolkit for training and fine-tuning sequence-to-sequence or generative adversarial network architectures to produce natural sounding speech. The system includes neural vocoder implementations that transform intermediate acoustic representations into final audio waveforms. It also features playback speed control to adjust the rate of synthesized speech output. The framework covers the end-to-end pipeline for speech synthesis, including audio data preprocessing to create
AudioGPT is an LLM-driven audio framework and processing suite that uses large language models to orchestrate neural audio pipelines. It functions as a multimodal audio generator and processing system, integrating a collection of pretrained models to handle speech synthesis, sound generation, and audio manipulation. The system is distinguished by its ability to generate audio from diverse inputs, including text and images, and its capacity to produce synchronized talking head videos. It also operates as a neural speech translator, converting spoken language between different tongues while pre
VibeVoice is a generative artificial intelligence platform designed for text-to-speech synthesis. It functions as a neural audio generation framework that converts written text into natural-sounding spoken audio, specifically engineered to maintain consistent vocal characteristics and narrative prosody across extended passages of content. The system distinguishes itself through its ability to generate long-form conversational speech while preserving speaker identity and linguistic content. By utilizing latent space disentanglement, the model separates speaker traits from the input text, allow
Zonos is a controllable audio synthesis engine and large language model for text-to-speech. It serves as a multilingual speech generator capable of producing audio in English, Japanese, Chinese, French, and German. The system provides zero-shot voice cloning, allowing the replication of specific human voices using short audio samples. It supports the capture of nuanced behaviors, such as whispering, and provides parametric control over speaking rate, pitch, frequency, and emotional tone. The project covers a broad range of expressive speech synthesis and custom audio generation capabilities,
seed-vc is an AI voice conversion tool and voice cloning system designed to transform the timbre, accent, and emotion of speech recordings. It provides a framework for replicating specific speaker identities and singing styles using short reference audio samples. The project includes a voice fine-tuning framework for training models on custom audio datasets to increase the accuracy of voice clones. It also features speech anonymization tools that remove unique speaker traits to produce a generic average voice for identity protection. The system covers a broad range of audio processing capabi
VoxCPM is a multilingual speech synthesis system and text-to-speech inference server. It functions as an AI voice cloning tool and a synthetic voice designer, capable of generating natural speech across global languages and regional dialects using a GPU-accelerated audio generator. The project features a speech model fine-tuning framework that supports both full parameter updates and low-rank adaptation for customizing voice characteristics. It enables high-fidelity voice cloning from reference audio, including cross-lingual voice transfer and acoustic environment mimicry, as well as the crea
This project is an expressive text-to-speech foundation model and voice cloning system designed to synthesize human-like speech with emotional nuance and high fidelity. It functions as a finetunable speech model that can generate audio mimicking a specific person using a reference voice sample. The system distinguishes itself through a high-performance inference engine that utilizes memory caching and hardware compilation to reduce latency during the audio generation process. It further allows for synthesis quality improvements by training the language model on custom datasets consisting of a
VoiceCraft is a neural speech generation and manipulation system consisting of a text-to-speech system, a voice cloning tool, and an audio inpainting engine. It uses a large language model approach to synthesize high-fidelity audio from text and replicate speaker identities. The system provides zero-shot voice cloning and speech editing capabilities, allowing users to modify spoken content within existing recordings. This includes an audio inpainting engine that replaces specific sections of audio with new speech while preserving the original acoustic characteristics and speaker identity. Th
MockingBird is an AI voice cloning tool and text-to-speech system designed to generate synthetic speech. It functions as a voice synthesis trainer for building custom models from audio datasets, a command-line generator for producing audio files, and a text-to-speech server for remote application integration. The project specializes in real-time voice cloning, which extracts vocal characteristics from short audio samples to mimic a target speaker's unique timbre. It utilizes reference-driven audio synthesis to condition pre-trained models on specific audio samples, allowing for the generation
WhisperSpeech is a multilingual speech synthesizer and neural text-to-speech system. It functions by inverting the Whisper model architecture to convert text into high-fidelity synthetic audio. The system enables voice cloning by using reference audio files to mimic specific speakers. It supports multilingual speech production, which includes the ability to generate audio across different languages and handle language switching within a single sentence. The project covers a broad range of speech capabilities, including text-to-speech generation and speech dataset preparation. It incorporates
Spark-TTS is a deep learning text-to-speech synthesis engine designed to convert written text into high-fidelity audio. It utilizes a transformer-based architecture and autoregressive sequence modeling to generate coherent speech, transforming linguistic input into natural-sounding waveforms through neural speech codec synthesis. The platform distinguishes itself through zero-shot voice cloning, which allows users to mimic a target speaker’s unique vocal identity using only a short reference audio sample without requiring additional model training. It also features cross-lingual phonetic mapp
TTS-WebUI is a web interface and speech synthesis manager designed to convert written text into spoken audio files. It serves as a self-hosted audio AI suite that allows users to configure speech synthesis models, manage speaker profiles, and generate audio through a graphical dashboard. The system functions as both a visual manager and a generative audio API, providing standardized endpoints and OpenAI-compatible request formats for external applications to trigger synthesis programmatically. It includes a plugin-based extension system that allows new tools and models to be added via externa
Voicevox is a text-to-speech synthesis software and audio production environment that converts written text into spoken audio using synthetic character voices. It functions as both a comprehensive editor for voice design and a standalone speech synthesis engine capable of generating audio via an API for integration into external applications. The project distinguishes itself by providing a singing voice synthesizer that uses a piano-roll interface for melodic vocal composition, including the ability to generate humming. It offers specialized prosody editing tools for the manual refinement of
ChatTTS is a conversational text-to-speech generative model designed to convert written dialogue into natural sounding audio. It functions as a multilingual speech synthesis framework capable of producing human-like audio across different languages and speaker profiles. The system is distinguished by its ability to generate interactive dialogue with realistic vocal nuances. It utilizes a speech nuance controller to insert specific tokens that trigger non-verbal elements, such as laughter, pauses, and interjections, during the synthesis process. The project includes a streaming audio generato
Kimi-Audio is a large language model audio foundation model designed to understand audio input and generate high-fidelity speech responses in real time. It functions as a unified system encompassing a text-to-speech synthesis engine and a speech-to-text transcription tool. The project enables real-time audio conversations through a multi-modal conversation loop and chunk-wise streaming detokenization to reduce playback latency. It provides controls over speech speed, accent, and emotional tone during conversational audio generation. The system covers audio intelligence capabilities, includin
OpenVoice is a multilingual text-to-speech framework and voice cloning AI model designed for high-fidelity voice replication and low-latency audio generation. It functions as an instant speech synthesis engine that converts text to audio while replicating a specific speaker's tone and color. The system is distinguished by its ability to perform cross-lingual cloning, allowing the vocal characteristics of a reference speaker to be applied to speech in different languages regardless of the original training data. It utilizes a decoupled representation to separate the physical identity of a voic
Orpheus-TTS is an open-source text-to-speech system that generates human-like audio with controllable emotional tone and the ability to clone voices from short audio samples. It is built on an architecture that treats speech generation as a language modeling task, using a large language model trained on text-speech pairs to produce audio tokens autoregressively. The system distinguishes itself through several key capabilities. It supports emotion-controllable speech synthesis by embedding emotional and intonation markers directly into text prompts, allowing the model to condition its output o
PaddleSpeech is a comprehensive toolkit of neural models for speech recognition, synthesis, and translation built on the PaddlePaddle deep learning framework. It provides a collection of frameworks and tools for converting spoken audio into written text, synthesizing natural audio from text, and performing direct speech translation. The toolkit includes specialized capabilities for keyword spotting to detect trigger words and speaker verification systems that extract unique voiceprints to identify and distinguish between individuals. It also features end-to-end translation tools that map audi
CSM is a conversational speech generation model and text-to-speech engine that converts text and audio inputs into synthetic speech. It utilizes a large language model architecture to predict and decode audio tokens for voice synthesis. The system functions as a zero-shot voice cloner, replicating specific speaker identities using short audio samples without requiring additional training. This enables precise control over speaker identity and the creation of synthetic speech that mimics a specific person. The model covers conversational speech synthesis and text-to-speech generation, transfo
Voice Pro is a comprehensive speech and audio processing toolkit that combines text-to-speech synthesis, voice cloning, speech recognition, and translation capabilities into a single application. At its core, the project enables users to generate natural-sounding speech from text, clone voices from short audio samples without requiring prior training data, and perform real-time speech translation across over 100 languages. The platform distinguishes itself through its integrated multimedia workflow, allowing users to download YouTube videos, extract audio, separate voice tracks, generate word
Bark Voice Cloning is a text-to-speech synthesis engine designed to generate natural-sounding audio and replicate specific vocal characteristics. The system utilizes a transformer-based autoregressive model to convert written text into high-fidelity speech, supporting multilingual output and expressive delivery. The project distinguishes itself through zero-shot voice cloning, which extracts speaker identity embeddings from short audio samples to condition the generative model without requiring extensive fine-tuning. It also provides specialized workflows for voice identity conversion, allowi
DiffSinger is an AI vocal synthesizer and neural audio generator designed to produce high-fidelity singing and speech. It functions as a text-to-speech system and a diffusion-based singing voice synthesis tool that transforms text and pitch into audible audio. The system utilizes a shallow diffusion mechanism and iterative noise refinement to generate realistic vocal performances. It incorporates specialized sampling plugins and numerical solvers to accelerate inference and reduce the time required to generate synthetic voices. The project covers acoustic modeling, mel-spectrogram synthesis,
KittenTTS is a neural text-to-speech engine and text-to-audio synthesis tool that converts written text into spoken audio using lightweight neural network models. It functions as both a speech synthesizer and an audio file generator, producing spoken audio for offline playback. The system includes a text normalization processor that expands numbers and abbreviations into full spoken words to improve the naturalness of the synthesized speech. It supports diverse voice options and provides the ability to adjust playback speed.