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MLXBits/ltx2.3-whisper-softly-spoken
ltx2.3-whisper-softly-spoken is a image-text-to-video model from MLXBits. Use it for the image-text-to-video task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Base model: LTX-2.3 dev (works on distilled) · Type: Audio-style LoRA · Rank: 32
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Updated Jun 14, 2026
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From the Hugging Face model README
Base model: LTX-2.3 dev (works on distilled) · Type: Audio-style LoRA · Rank: 32
LTX-2.3 can generate dialogue, multi-speaker scenes, and full dynamic range audio including screaming — but it cannot whisper. This LoRA adds two quiet vocal registers to the model:
The LoRA targets only the three attention modules that write to the audio branch (audio_attn1, audio_attn2, video_to_audio_attn). Video output is provably unchanged — no visual fighting, no style drift.
Load at strength 1.0. The register is controlled entirely by the manner keyword in your prompt — no special strength tuning needed.
| Register | Female | Male |
|---|---|---|
| Whispering | (woman, whispering) | (man, whispering quietly) |
| Soft-spoken | (woman, speaking softly) | (man, speaking softly) |
Note: Male whisper requires the extra word
quietlyto tip the model over.(man, whispering)alone produces soft-spoken, not true whisper.
Follow the LTX-2.3 dialogue caption style:
a [scene description], ([gender], [manner]): "[what they say]"
Examples:
a woman sitting close to a microphone in warm dim lighting, (woman, whispering): "close your eyes and listen"
a man at a desk late at night, (man, speaking softly): "I've been thinking about this all day"
a woman doing a skincare routine, (woman, whispering quietly): "this is my favourite step"
Using the LoRA without any manner keyword defaults to soft-spoken — a subtle volume-softening effect on whatever the base model would have generated. Useful as a gentle "quieter audio" modifier.
| Base model | LTX-2.3 dev |
| Epochs | ~27 |
| Steps | 2000 |
| Rank / Alpha | 32 / 32 |
| Target modules | audio_attn1, audio_attn2, video_to_audio_attn |
| Training resolution | 192×192, 97 frames (~4s @ 24fps) |
| Dataset | 74 clips, 8 voices (4F / 4M), 2 registers each |
Clips were 4-second segments sourced from ASMR content across 8 speakers — 4 female (2 soft-spoken, 2 whisper) and 4 male (2 soft-spoken, 2 whisper). Captions used Whisper ASR transcription in (gender, manner): "transcript" format.