alpha-ai/SpeakSpace-Assistant-v1-3B

<div align="center"> <img src="https://huggingface.co/alphaaico/SpeakSpace-Assistant-v1-3B/resolve/main/SpeakSpace_thumbnail.png" alt="SpeakSpace Assistant" style="width: 600px; height: auto; object-position: center top;"> </div>

SpeakSpace-Assistant-v1-3B

Alpha AI (www.alphaai.biz) fine-tuned canopylabs/orpheus-3b-0.1-ft to create SpeakSpace-Assistant-v1-3B — an English-only, single-speaker voice assistant model. The fine-tune uses custom voice recordings plus the Elise dataset (~3 hours, single-speaker English speech). Transcripts were augmented with emotion/expression tags like <sigh> and <laughs>, added as special tokens in the Orpheus tokenizer.

⚠️ Important: This model is intended for research, prototyping, and internal product demos. Do not use it to impersonate a real person without explicit consent. Review base-model and dataset licenses before commercial use.

TL;DR

• —Base: canopylabs/orpheus-3b-0.1-ft (~3B params).
• —Data: Custom Alpha AI dataset + MrDragonFox/Elise (English, ~3 hours).
• —Objective: Produce natural, expressive speech with inline emotion cues (<laughs>, <sigh>).
• —Language: English only.
• —Repo: Suggested as alpha-ai/SpeakSpace-Assistant-v1-3B.

Intended Use & Limitations

Intended use:

• —Internal voice assistants and demos.
• —Research on expressive TTS and emotion-tag-conditioned speech.
• —Applications where transcripts include small expressive markers.

Limitations:

• —Not multi-speaker or multilingual.
• —Quality limited by dataset size (~3 hrs + custom data).
• —Requires Orpheus vocoder/decoder to convert tokens to waveform.
• —Do not deploy for impersonation without explicit consent.

Model Details

• —Family: Orpheus 3B (decoder-based speech model).
• —Tokenizer: Extended with special tokens (<laughs>, <sigh>).
• —Fine-tuning: Supervised finetuning on audio–transcript pairs.
• —Output: Discrete audio tokens; decode with Orpheus vocoder.

Data

Sources:

• —Alpha AI custom speech dataset.
• —MrDragonFox/Elise (~3 hrs English single-speaker).

Preprocessing:

• —Aligned utterances with transcripts.
• —Expression tags inserted inline.
• —Special tokens added to tokenizer.

Prompt & Input Format

Model accepts text input with optional inline expressions:

Hello! <laughs> I can help with your schedule today.

Workflow: tokenize → generate audio tokens → decode via vocoder.

Training Summary

• —Objective: Predict audio tokens from transcripts (with expression markers).
• —Loss: Causal LM loss.
• —Optimizer: AdamW or AdamW-8bit (please add exact values).
• —Hyperparameters: Learning rate, batch size, gradient accumulation, seed — to be filled with actual values.

Evaluation

Recommended:

• —MOS (Mean Opinion Score): naturalness & expressiveness.
• —Speaker similarity: ABX or MOS vs. ground truth.
• —Intelligibility: WER via ASR.
• —Emotion accuracy: Human rating of <laughs>, <sigh> cues.

Add quantitative results when available.

Safety & Responsible Use

• —Use only with documented consent for training voices.
• —Guard against impersonation risks.
• —Consider watermarking or metadata tagging for provenance.
• —Do not generalize beyond training speaker’s identity.

License & Attribution

• —Base model: canopylabs/orpheus-3b-0.1-ft (review base license).
• —Dataset: MrDragonFox/Elise (check dataset license).
• —Fine-tune: Ensure compatibility of licenses.

Suggested citation:

SpeakSpace-Assistant-v1-3B — fine-tune of canopylabs/orpheus-3b-0.1-ft on Alpha AI custom dataset + MrDragonFox/Elise.

Acknowledgements

• —canopylabs — Orpheus base model.
• —MrDragonFox — Elise dataset.
• —Alpha AI research & engineering team.

Contact

Questions, issues, or collaborations:

• —Open a discussion on the Hugging Face repo.
• —Enterprise contact (Alpha AI): www.alphaai.biz | corporate@alphaai.biz
• —Enterprise contact (SpeakSpace): www.speakspace.co | connect@speakspace.co