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3 repositorios

Awesome GitHub RepositoriesAudio

Collections of audio recordings used for training and fine-tuning voice synthesis models.

Distinct from Training Datasets: Specifically targets audio data for speech models rather than general text collections for LLMs.

Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Audio. Refine with filters or upvote what's useful.

Awesome Audio GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • babysor/mockingbirdAvatar de babysor

    babysor/MockingBird

    36,903Ver en GitHub↗

    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

    Enables the optimization of voice synthesizers through training on specific audio datasets.

    Pythonaideep-learningpytorch
    Ver en GitHub↗36,903
  • svc-develop-team/so-vits-svcAvatar de svc-develop-team

    svc-develop-team/so-vits-svc

    28,097Ver en GitHub↗

    This project is a singing voice conversion tool based on VITS generative modeling. It transforms the identity of a singing voice to a target speaker while preserving the original melody, lyrics, and intonation. The system distinguishes itself through hybrid voice synthesis, allowing for the blending of multiple speaker identities via linear model interpolation. It utilizes cluster-based feature retrieval to increase target voice similarity and employs a diffusion probabilistic model as a post-processor to remove electronic artifacts and improve vocal clarity. The software covers a broad rang

    Provides capabilities to import audio files or compressed archives from local systems for training.

    Python
    Ver en GitHub↗28,097
  • snakers4/silero-vadAvatar de snakers4

    snakers4/silero-vad

    8,209Ver en GitHub↗

    Silero VAD is a voice activity detection model and deep learning speech classifier designed to distinguish human speech from silence across diverse languages and noisy environments. It functions as a pre-trained neural network capable of identifying speech segments within both static audio recordings and real-time data streams. The project includes a language identification tool for classifying spoken languages and a framework for fine-tuning audio models. It provides utilities for optimizing detection thresholds using validation datasets and retraining the model with custom labeled audio to

    Retrieves curated datasets of audio files with pre-calculated timestamps and language codes for model training.

    Pythononnxonnx-runtimeonnxruntime
    Ver en GitHub↗8,209
  1. Home
  2. Artificial Intelligence & ML
  3. Large-Scale Model Training
  4. Training Datasets
  5. Audio

Explorar subetiquetas

  • Ingestion PipelinesMechanisms for importing and uploading raw audio recordings for model training. **Distinct from Audio:** Focuses on the upload and ingestion of local audio files into the training pipeline, rather than the dataset collection itself