Projects sharing features with WhisperSpeech

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

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

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

Supertonic is an on-device neural text-to-speech engine that runs entirely locally without cloud dependencies or GPU acceleration. It converts written text into natural-sounding speech across 31 languages with automatic language detection and a fallback model for unsupported locales. The engine provides expressive speech control through inline prosody tags that dynamically adjust pitch, rate, and tone during synthesis. It supports voice cloning from a short reference audio clip by extracting a speaker embedding vector, and offers a selection of pre-built voices tuned for different use cases.

This Python SDK provides a comprehensive toolkit for synthetic audio generation, voice cloning, and the development of conversational AI agents. It enables the creation of lifelike spoken audio from text, the replication of human voices through custom cloning, and the deployment of real-time voice agents capable of interacting with external large language models. The library distinguishes itself through deep integration of conversational AI capabilities, including the design of agent personas and the execution of real-time actions via APIs. It supports professional-grade audio production thro

Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag

Neutts is a neural text-to-speech engine designed for real-time streaming output on edge devices such as phones and laptops. It supports voice cloning from short audio references, enabling zero-shot reproduction of a target speaker's voice, and can be fine-tuned or retrained from scratch for custom voices and styles. The system distinguishes itself through a decoder-only architecture that halves memory and accelerates generation on constrained hardware, combined with quantized model inference for reduced memory footprint. Its streaming decoder loop interleaves synthesis with playback, deliver

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

Pocket-tts is a text-to-speech server and neural speech synthesizer that converts written text into audible speech. It includes a CPU-optimized inference engine and a voice cloning tool capable of analyzing audio samples to reproduce specific speaker characteristics. The system differentiates itself through the use of dynamic int8 quantization to reduce memory usage and increase generation speed on processors. It supports real-time speech synthesis by streaming audio chunks incrementally and utilizes voice state caching to store processed embeddings as portable files, bypassing redundant proc

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

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

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

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

Dia is a generative AI audio tool and text-to-speech synthesis engine designed for the production-ready deployment of machine learning models. It provides a framework for creating lifelike synthetic speech by conditioning generation on reference audio samples to replicate specific vocal characteristics, emotional tones, and delivery styles. The system distinguishes itself through its ability to perform custom voice cloning and precise control over audio output. Users can adjust generation parameters such as temperature and guidance scale to modify the pacing, creativity, and style of the synt

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

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

VALL-E-X is a neural speech synthesis framework and zero-shot text-to-speech engine. It functions as a multilingual synthesizer capable of generating natural human speech with control over emotion, pitch, and prosody. The project specializes in zero-shot voice cloning and cross-lingual voice replication, allowing the system to produce personalized speech in multiple target languages using short audio samples without additional training. It further enables cross-language accent manipulation and the ability to match the emotional tone and acoustic environment of a provided prompt. The implemen

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

Amphion is an audio generation toolkit designed for the research and development of models that synthesize speech, music, and environmental sound effects. It provides a standardized framework for reproducible audio synthesis, incorporating a text-to-speech engine and a voice conversion framework. The project specializes in transforming audio identities, allowing for the modification of speaker accents and voice identities while preserving original rhythm and style. It also includes capabilities for singing voice synthesis and the generation of environmental soundscapes from text descriptions

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

Higgs-audio is a generative text-to-speech engine that transforms text into natural conversational speech using large language model architectures. It functions as a multilingual speech synthesizer capable of generating high-fidelity audio across different languages with control over emotional tone and prosody. The system includes a voice cloning tool that creates synthetic replicas of specific speakers from short audio samples without requiring extensive model training. It also provides a streaming audio API designed to deliver generated speech incrementally to minimize playback delay. The

VITS-fast-fine-tuning is a pipeline for adapting speech synthesis models to specific target voices using small audio datasets. It functions as a fast speaker adaptation tool and a multilingual speech synthesizer capable of generating spoken audio across different languages. The system provides a framework for many-to-many voice conversion, transforming the identity of one speaker into another while preserving the original linguistic content. It allows for the adaptation of a voice for text-to-speech by fine-tuning a pre-trained model with audio clips or video sources. The project covers end-

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

RealtimeTTS is a real-time text-to-speech engine and stream processor designed to convert text or token streams into audio playback with minimal latency. It provides a programmatic interface for managing audio streams, synthesis progress, and the integration of local or cloud-based speech engines. The system includes a neural voice cloning tool that generates synthetic speech by extracting acoustic features from reference audio samples. It utilizes a provider-based abstraction to route synthesis requests across different neural models and cloud APIs. The project covers a range of functional

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

Sherpa-ONNX is an ONNX-based speech processing toolkit that provides a local speech recognition engine, an on-device voice synthesis tool, and a speaker identification framework. It is designed as a cross-platform speech API that enables speech-to-text, text-to-speech, and speaker verification tasks to be executed locally on a device without requiring network access. The project is distinguished by its ability to perform zero-shot voice cloning and speaker diarization on-device. It supports a wide range of hardware accelerations, including GPU and various NPU architectures, and provides a Web