Showing 4 open source projects for "speech processing"

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    NVIDIA NeMo

    NVIDIA NeMo

    Toolkit for conversational AI

    ...Supported models: Jasper, QuartzNet, CitriNet, Conformer-CTC, Conformer-Transducer, Squeezeformer-CTC, Squeezeformer-Transducer, ContextNet, LSTM-Transducer (RNNT), LSTM-CTC. NGC collection of pre-trained speech processing models.
    Downloads: 0 This Week
    Last Update:
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  • 2
    WhisperJAV

    WhisperJAV

    Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD

    WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. WhisperJAV introduces...
    Downloads: 22 This Week
    Last Update:
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  • 3
    Streamer-Sales

    Streamer-Sales

    LLM Large Model of Selling Anchor

    Streamer-Sales is an open-source large language model system designed specifically for e-commerce live streaming and automated product promotion. The project focuses on generating persuasive product descriptions and live presentation scripts that mimic the style of professional online sales hosts. By analyzing product characteristics and marketing information, the model can produce engaging explanations that emphasize benefits, features, and emotional appeal to encourage viewers to make...
    Downloads: 0 This Week
    Last Update:
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  • 4
    Fun Audio Chat

    Fun Audio Chat

    Large Audio Language Model built for natural interactions

    Fun Audio Chat is an interactive voice-first conversational AI platform designed to let users engage in natural spoken dialogue with large language models in real time, turning speech into context-aware responses while maintaining a smooth back-and-forth experience. It combines speech recognition, audio processing, and AI generation so users can speak simply and receive spoken replies, enabling applications such as virtual assistants, voice bots, and hands-free chat interfaces. The system supports dynamic audio input and output, meaning it can handle different voices, tones, and conversational contexts without forcing users into typed interactions. ...
    Downloads: 0 This Week
    Last Update:
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