Audio-to-Audio
Moshi
Safetensors
Hindi
speech-to-speech
hindi
conversational-ai
audio
full-duplex
duplex-dialogue
indian-languages
Instructions to use JoshTalksAI/Human-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Moshi
How to use JoshTalksAI/Human-1 with Moshi:
# pip install moshi # Run the interactive web server python -m moshi.server --hf-repo "JoshTalksAI/Human-1" # Then open https://localhost:8998 in your browser
# pip install moshi import torch from moshi.models import loaders # Load checkpoint info from HuggingFace checkpoint = loaders.CheckpointInfo.from_hf_repo("JoshTalksAI/Human-1") # Load the Mimi audio codec mimi = checkpoint.get_mimi(device="cuda") mimi.set_num_codebooks(8) # Encode audio (24kHz, mono) wav = torch.randn(1, 1, 24000 * 10) # [batch, channels, samples] with torch.no_grad(): codes = mimi.encode(wav.cuda()) decoded = mimi.decode(codes) - Notebooks
- Google Colab
- Kaggle
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### Human Evaluation
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| Dataset | Ratings | Female | Male | 18–25 | 25–30 | 30–35 |
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| Speech Dialogue Eval. | 2,125 | 34 | 29 | 28 | 19 | 8 |
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**Perceptual quality:**
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### Human Evaluation
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130 evaluators completed 2,125 rating tasks comparing human speech with model responses. Each instance contained two audio samples (Voice A: Human, Voice B: Model) rated on 5-point Likert scales for naturalness and clarity.
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**Perceptual quality:**
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