LTX 2.3 Trainer (V2) - Audio-to-Audio
LTX 2.3 Trainer transforms any audio into new audio.
A tradução deste card ainda não está disponível; parte do conteúdo aparece em inglês.
LTX 2.3 Trainer is an audio-to-audio model that takes an input sound and generates a transformed version based on your creative direction. It works with music, speech, sound effects, and ambient audio, making it a versatile tool for sound design, remixing, and audio experimentation.
Use it when you want to reinterpret an existing recording — turn a vocal melody into a synth lead, change a drum loop’s genre, or add atmospheric texture to a field recording. The model preserves the core structure of the original while applying your stylistic instructions.
What makes LTX 2.3 Trainer distinctive is its ability to understand both the source audio and a text prompt simultaneously, allowing for fine-grained control over the transformation. It can also generate variations from a single seed audio, giving you multiple creative options from one starting point.
- Remixing music tracks into new genres
- Transforming vocal melodies into instrument sounds
- Adding effects and textures to field recordings
- Creating audio variations for game sound design
- Repurposing speech into musical phrases
Accurately applies a described style to any input audio while keeping the original structure.
Generates multiple distinct outputs from the same source audio using different prompts.
Works with music, voice, sound effects, and ambient recordings without specialized preprocessing.
- Use clean, isolated audio for best transformation results.
- Experiment with descriptive style prompts like 'lo-fi hip hop' or 'cinematic strings'.
- Start with a short audio clip (5-15 seconds) to test the transformation before processing longer files.
- Adjust the guidance scale to control how strictly the model follows your prompt versus the original audio.
- May introduce artifacts on very complex or noisy source audio.
- Cannot perfectly preserve all nuances of the original recording.
- Output quality depends on clarity of the input audio and prompt specificity.
Transform this acoustic guitar fingerpicking into a lush cinematic string ensemble.
Convert this spoken word into a haunting choral harmony with layered voices.
Turn this electronic drum pattern into an energetic live percussion performance with congas and bongos.
A number that sets the starting point for generation — same seed and prompt gives the same result.
Number of refinement steps — more steps can improve quality but increase processing time.
Limits the model to consider only the most likely options — lower values make output more focused.
Length of the output audio in seconds — longer durations may take more time to generate.
Controls randomness — higher values produce more unexpected results, lower values are more predictable.
How strongly the model follows your prompt — higher values stick closer to the description.
Os preços exibidos são o que você paga na Muitto. Sem surpresas.
What kind of audio can I use as input?
Any audio file works, but cleaner recordings with less background noise produce better results.
How long does a transformation take?
Processing time depends on the length of the input audio and the complexity of the transformation.
Can I use the same input to get different outputs?
Yes, by changing the prompt or adjusting parameters like temperature and seed you can get endless variations.