9. Conclusion & Future Work
9.1 Summary
We have presented the Inner Voice framework for extracting and applying a perceptual style delta vector using CAM+
+ speaker embeddings and Seed-VC voice conversion. The pipeline is fully implemented with a Gradio web interface,
real-time metrics, and open-source release. The key finding — CAM++ spectral invariance — reveals both a
limitation and an insight: speaker verification encoders are fundamentally unsuitable for perceptual style extraction
because they are trained to discard spectral information.
9.2 Immediate Next Steps (July 2025)
1. target_mel override (highest impact). The CFM model’s target_mel conditioning carries stronger speaker
information than the style embedding. By overriding both the style embedding AND the target_mel with a filtered
reference, we can produce a more distinct Perceived output. This is the most promising direction for improving
audibility.
2. Aggressive filter parameters. Increasing filter strength (lowpass at 2 kHz, EQ +12 dB) will produce a larger ΔV
with potentially greater perceptual impact.
9.3 Medium-term (August–October 2025)
3. Replace CAM++ with WavLM or HuBERT. Self-supervised speech models like WavLM [10] and HuBERT are
trained on raw audio without speaker verification objectives. They may retain more spectral detail and produce larger,
more meaningful ΔV vectors.
4. Subject study (n > 10). The current study uses a single recording from one subject. A multi-subject study with
perceptual listening tests will determine whether ΔV carries any speaker-generalizable information.
9.4 Long-term (November–December 2025)
5. Clinical pilot. Collaboration with a medical institution to test the pre-surgery ΔV recording protocol with laryngeal
cancer patients.
6. Publication. Target conferences: ICASSP (IEEE International Conference on Acoustics, Speech and Signal
Processing) or ISMIR (International Society for Music Information Retrieval) workshop track.
