01 / OVERVIEW
PROJECT OVERVIEW
DubForge is a speech, audio and dubbing system direction.
The project focus is not only moving words between tracks, but preserving the character and expression carried by a voice.
02 / USE CASES
DUBBING USE CASES
UC-01
SEPARATE SOURCE AUDIO
Separate dialogue from music and effects before later speech processing.
UC-02
IDENTIFY SPEAKERS
Use utterances and speaker profiles to keep the voice context attached to each segment.
UC-03
TRANSLATE WITH CONTEXT
Translate dialogue while retaining speaker identity and performance context.
UC-04
SELECT VOICE REFERENCES
Match a speaker to a reference bank for the next voice-generation stage.
UC-05
REBUILD THE MIX
Explore a translated track that keeps voice character and expression as close as possible.
03 / AUDIO FLOW
DUBBING PIPELINE
Speech and dubbing path
- SPEECH INPUT
- AUDIO PROCESSING
- VOICE CHARACTER
- EXPRESSION
- DUBBED OUTPUT
04 / SYSTEM SCOPE
END-TO-END DEMO SCOPE
STATE ACTIVE R&D / END-TO-END DEMO DEVELOPMENT
PIPELINE SEPARATION / TRANSCRIPTION / SEGMENTATION / SPEAKER PROFILE / TRANSLATION / VOICE / MIX
BOUNDARY FINAL COMPLETE DUBBING PRODUCT IS STILL IN DEVELOPMENT
05 / ENGINEERING
VOICE PROCESSING DECISIONS
E-01
TIMESTAMPED UTTERANCES
Use faster-whisper large-v3 output and word timestamps to create atomic speech units.
E-02
SPEAKER PROFILES
Use ECAPA-TDNN embeddings and canonical references to retain speaker context.
E-03
PERFORMANCE SIGNAL
Treat expression and delivery as part of the voice problem, not just translation text.
06 / TECH STACK
TECHNICAL LAYER
- Python
- Faster-Whisper large-v3
- ECAPA-TDNN
- Audio Separation
- Speaker Embeddings
07 / STATUS
PROJECT STATE
STATE ACTIVE R&D / END-TO-END DEMO DEVELOPMENT
SCOPE SPEECH / AUDIO / DUBBING PIPELINE