7 projects for "audio processing" with 2 filters applied:

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    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

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  • 1
    VibeVoice

    VibeVoice

    Open-source multi-speaker long-form text-to-speech model

    VibeVoice-1.5B is Microsoft’s frontier open-source text-to-speech (TTS) model designed for generating expressive, long-form, multi-speaker conversational audio such as podcasts. Unlike traditional TTS systems, it excels in scalability, speaker consistency, and natural turn-taking for up to 90 minutes of continuous speech with as many as four distinct speakers. A key innovation is its use of continuous acoustic and semantic speech tokenizers operating at an ultra-low frame rate of 7.5 Hz, enabling high audio fidelity with efficient processing of long sequences. ...
    Downloads: 12 This Week
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  • 2
    LTX-Video

    LTX-Video

    Official repository for LTX-Video

    LTX-Video is a sophisticated multimedia processing framework from Lightricks designed to handle high-quality video editing, compositing, and transformation tasks with performance and scalability. It provides runtime components that efficiently decode, encode, and manipulate video streams, frame buffers, and audio tracks while exposing a rich API for building customized editing features like transitions, effects, color grading, and keyframe automation.
    Downloads: 5 This Week
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  • 3
    Vidi2

    Vidi2

    Large Multimodal Models for Video Understanding and Editing

    ...The system is built with open-source release in mind, giving developers access to model code, inference scripts, and evaluation pipelines so they can reproduce research results or integrate Vidi into their own video-processing workflows.
    Downloads: 1 This Week
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  • 4
    CSM (Conversational Speech Model)

    CSM (Conversational Speech Model)

    A Conversational Speech Generation Model

    The CSM (Conversational Speech Model) is a speech generation model developed by Sesame AI that creates RVQ audio codes from text and audio inputs. It uses a Llama backbone and a smaller audio decoder to produce audio codes for realistic speech synthesis. The model has been fine-tuned for interactive voice demos and is hosted on platforms like Hugging Face for testing. CSM offers a flexible setup and is compatible with CUDA-enabled GPUs for efficient execution.
    Downloads: 8 This Week
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  • 5
    DiffRhythm

    DiffRhythm

    Di♪♪Rhythm: Blazingly Fast & Simple End-to-End Song Generation

    DiffRhythm is an open-source, diffusion-based model designed to generate full-length songs. Focused on music creation, it combines advanced AI techniques to produce coherent and creative audio compositions. The model utilizes a latent diffusion architecture, making it capable of producing high-quality, long-form music. It can be accessed on Huggingface, where users can interact with a demo or download the model for further use. DiffRhythm offers tools for both training and inference, and its...
    Downloads: 13 This Week
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  • 6
    Denoiser

    Denoiser

    Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)

    ...The implementation includes data augmentation techniques applied to the raw waveforms (e.g. noise mixing, reverberation) to improve model robustness and generalization to diverse noise types. The project supports both offline denoising (batch inference) and live audio processing (e.g. via loopback audio interfaces), making it practical for real-time use in calls or recording. The codebase includes training and evaluation scripts, configuration management via Hydra, and pretrained models on standard noise datasets.
    Downloads: 0 This Week
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  • 7
    mms-300m-1130-forced-aligner

    mms-300m-1130-forced-aligner

    CTC-based forced aligner for audio-text in 158 languages

    ...The alignment pipeline includes audio processing, emission generation, tokenization, and span detection, making it suitable for speech analysis, transcription syncing, and dataset creation. This model is especially useful for researchers and developers working with low-resource languages or building multilingual speech systems.
    Downloads: 0 This Week
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