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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 main features of kyutai-labs/pocket-tts are: Text-to-Speech, Voice Cloning, Voice Cloning Tools, CPU Inference Runtimes, C++ Inference Backends, CPU Inference Quantizers, Real-Time Speech Synthesis, Incremental Synthesis.
Projects with overlapping indexed features include: moonshotai/kimi-audio — Kimi-Audio is a large language model audio foundation model designed to understand audio input and generate… babysor/mockingbird — MockingBird is an AI voice cloning tool and text-to-speech system designed to generate synthetic speech. It functions… coqui-ai/tts — This project is a deep learning text-to-speech toolkit used for training and deploying neural speech synthesis models.… openbmb/voxcpm — VoxCPM is a multilingual speech synthesis system and text-to-speech inference server. It functions as an AI voice… elevenlabs/elevenlabs-python — This Python SDK provides a comprehensive toolkit for synthetic audio generation, voice cloning, and the development of… bytedance/megatts3 — MegaTTS3 is a bilingual speech synthesis system that generates natural-sounding speech in Chinese and English,…
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
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
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.
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