Showing 4 open source projects for "flipper zero control"

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  • 1
    GLM-TTS

    GLM-TTS

    Controllable & emotion-expressive zero-shot TTS

    ...GLM-TTS also supports phoneme-level control and hybrid text + phoneme input, giving developers precise control over pronunciation critical for multilingual or polyphone­-rich languages.
    Downloads: 0 This Week
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  • 2
    MOSS-TTS Family

    MOSS-TTS Family

    MOSS‑TTS Family open‑source speech and sound generation model

    ...The project is designed for complex real-world use cases where a single speech model may not be enough. Its flagship model focuses on stable long speech generation, multilingual and code-switched synthesis, pronunciation control, and zero-shot voice cloning. The broader family also includes dialogue generation, prompt-based voice creation, streaming voice-agent support, and a unified audio tokenizer. It is especially useful for developers building dubbing, podcasts, audiobooks, voice assistants, character voices, and creative audio tools.
    Downloads: 0 This Week
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  • 3
    Step-Audio-EditX

    Step-Audio-EditX

    LLM-based Reinforcement Learning audio edit model

    Step-Audio-EditX is an open-source, 3 billion-parameter audio model from StepFun AI designed to make expressive and precise editing of speech and audio as easy as text editing. Rather than treating audio editing as low-level waveform manipulation, this model converts speech into a sequence of discrete “audio tokens” (via a dual-codebook tokenizer) — combining a linguistic token stream and a semantic (prosody/emotion/style) token stream — thereby abstracting audio editing into high-level...
    Downloads: 0 This Week
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  • 4
    PRM800K

    PRM800K

    800,000 step-level correctness labels on LLM solutions to MATH problem

    ...Data are stored as newline-delimited JSONL files tracked with Git LFS, where each line is a full solution sample that can contain many step-level labels and rich metadata such as labeler UUIDs, timestamps, generation identifiers, and quality-control flags. Each labeled step can include multiple candidate completions with ratings of -1, 0, or +1, optional human-written corrections (phase 1), and a chosen completion index, along with a final finish reason such as found_error, solution, bad_problem, or give_up.
    Downloads: 1 This Week
    Last Update:
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