Showing 40 open source projects for "speaker"

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  • 1
    Coqui TTS

    Coqui TTS

    A deep learning toolkit for Text-to-Speech, battle-tested in research

    ...TTS comes with pre-trained models, tools for measuring dataset quality and is already used in 20+ languages for products and research projects. High-performance Deep Learning models for Text2Speech tasks. Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech). Speaker Encoder to compute speaker embeddings efficiently. Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN) Fast and efficient model training. Detailed training logs on the terminal and Tensorboard. Support for Multi-speaker TTS. Efficient, flexible, and lightweight but feature complete Trainer API. ...
    Downloads: 16 This Week
    Last Update:
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  • 2
    vits_chinese

    vits_chinese

    Best practice TTS based on BERT and VITS

    vits_chinese is an implementation of the VITS end-to-end text-to-speech (TTS) architecture tailored for Chinese (and possibly multilingual) speech synthesis. VITS is a model combining variational autoencoders (VAEs), normalizing flows, adversarial learning, and a stochastic duration predictor — a design that enables generation of natural, expressive speech, capturing variations in rhythm and prosody. By customizing or porting VITS for Chinese, this project aims to produce high-quality TTS...
    Downloads: 2 This Week
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  • 3
    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. VALL-E-X supports zero-shot cross-lingual synthesis, meaning a monolingual speaker’s voice can be used to speak other languages without additional training. ...
    Downloads: 3 This Week
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  • 4
    wukong-robot

    wukong-robot

    Chinese voice dialogue robot/smart speaker project

    wukong-robot is a Chinese voice assistant / smart speaker project built to let makers and hackers design highly customizable voice-controlled devices. It combines wake-word detection, automatic speech recognition, natural language understanding, and text-to-speech into a single framework aimed at the Chinese-speaking ecosystem. The project is positioned as a simple, flexible, and elegant platform that can run on devices like Raspberry Pi and other Linux-based boards, making it suitable for DIY smart speakers and home-automation hubs. ...
    Downloads: 1 This Week
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  • 5
    lora-svc

    lora-svc

    Singing voice change based on whisper, lora for singing voice clone

    singing voice change based on whisper, and lora for singing voice clone. You will feel the beauty of the code from this project. Uni-SVC main branch is for singing voice clone based on whisper with speaker encoder and speaker adapter. Uni-SVC main target is to develop lora for SVC. With lora, maybe clone a singer just need 10 stence after 10 minutes train. Each singer is a plug-in of the base model.
    Downloads: 0 This Week
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  • 6
    VALL-E

    VALL-E

    PyTorch implementation of VALL-E (Zero-Shot Text-To-Speech)

    ...VALL-E emerges in-context learning capabilities and can be used to synthesize high-quality personalized speech with only a 3-second enrolled recording of an unseen speaker as an acoustic prompt. Experiment results show that VALL-E significantly outperforms the state-of-the-art zero-shot TTS system in terms of speech naturalness and speaker similarity. In addition, we find VALL-E could preserve the speaker's emotion and acoustic environment of the acoustic prompt in synthesis.
    Downloads: 1 This Week
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  • 7
    VoiceSmith

    VoiceSmith

    [WIP] VoiceSmith makes training text to speech models easy

    ...It fine-tunes a pretty solid text to speech pipeline based on a modified version of DelightfulTTS and UnivNet on your dataset. Both models were pretrained on a proprietary 5000 speaker dataset. It also provides some tools for dataset preprocessing like automatic text normalization. Windows (only CPU supported currently) or any Linux based operating system. If you want to run this on macOS you have to follow the steps in build from source in order to create the installer. This is untested since I don't currently own a Mac. ...
    Downloads: 0 This Week
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  • 8
    VITS

    VITS

    Conditional Variational Autoencoder with Adversarial Learning

    ...This architecture enables parallel generation (fast inference) while achieving speech quality that rivals or surpasses many two-stage systems. The repository provides training and inference pipelines for common datasets such as LJ Speech (single-speaker) and VCTK (multi-speaker), including filelists, configs, and preprocessing scripts. It also includes monotonic alignment search code and g2p preprocessing, which are crucial components for aligning text and speech in an end-to-end setup.
    Downloads: 0 This Week
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  • 9
    Multilingual Speech Synthesis

    Multilingual Speech Synthesis

    An implementation of Tacotron 2 that supports multilingual experiments

    ...It presents a model combining ideas from Learning to speak fluently in a foreign language: Multilingual speech synthesis and cross-language voice cloning, End-to-End Code-Switched TTS with Mix of Monolingual Recordings, and Contextual Parameter Generation for Universal Neural Machine Translation. We provide data for comparison of three multilingual text-to-speech models. The first shares the whole encoder and uses an adversarial classifier to remove speaker-dependent information from the encoder. The second has separate encoders for each language.
    Downloads: 0 This Week
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  • 10
    Resemblyzer

    Resemblyzer

    A python package to analyze and compare voices with deep learning

    ...Its main value is making speaker representation accessible through a simple Python workflow.
    Downloads: 3 This Week
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  • 11
    Deepvoice3_pytorch

    Deepvoice3_pytorch

    PyTorch implementation of convolutional neural networks

    An open source implementation of Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning.
    Downloads: 0 This Week
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  • 12
    DC-TTS

    DC-TTS

    TensorFlow Implementation of DC-TTS: yet another text-to-speech model

    ...Training scripts, data loaders, and hyperparameter configurations are provided to reproduce results on several datasets, including LJ Speech for English, a Korean single-speaker dataset, and audiobook data from Nick Offerman and Kate Winslet.
    Downloads: 0 This Week
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  • 13
    Lip Reading

    Lip Reading

    Cross Audio-Visual Recognition using 3D Architectures

    ...Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the extracted information from one modality to improve the recognition ability of the other modality by complementing the missing information. The essential problem is to find the correspondence between the audio and visual streams, which is the goal of this work. ...
    Downloads: 4 This Week
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  • 14

    Distant Speech Recognition

    Beamforming and Speech Recognition Toolkit

    BTK contains C++ and Python libraries that implement speech processing and microphone array techniques such as speech feature extraction, speech enhancement, speaker tracking, beamforming, dereverberation and echo cancellation algorithms. The Millennium ASR provides C++ and python libraries for automatic speech recognition. The Millennium ASR implements a weighted finite state transducer (WFST) decoder, training and adaptation methods. These toolkits are meant for facilitating research and development of automatic distant speech recognition.
    Downloads: 1 This Week
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  • 15
    Dia-1.6B

    Dia-1.6B

    Dia-1.6B generates lifelike English dialogue and vocal expressions

    ...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. 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. ...
    Downloads: 0 This Week
    Last Update:
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