Research & development
We investigate the edge cases of speech and sound so the systems built from them are more robust, more transparent, and more useful in the conditions analysts actually work in.
Phonix Lab' research agenda is shaped by the recordings analysts actually encounter — not the clean, studio-quality audio that dominates standard benchmarks. We focus on reproducible evaluation, appropriate data governance, and transparent model limits that travel with every output.
Pushing transcription accuracy and alignment under dialect variation, low-resource language conditions, heavy code-switching, channel noise, and compression artifacts — the conditions that break off-the-shelf systems.
Advancing diarization, speaker representations, and conversation-level structure in naturally occurring, non-studio audio — including overlapping speech, interrupted turns, and multi-channel field recordings.
Building representations that preserve interpretable signal cues while supporting scalable retrieval, continuous monitoring, and structured analyst review workflows.
Developing evaluation frameworks, model documentation standards, and human-review practices for speech and acoustic systems operating in high-consequence environments.
We assess models against the context they are expected to operate in — not only by aggregate scores on public datasets. We do not position model outputs as proof of identity, intent, deception, or psychological state. Our systems are designed to support trained human review under appropriate governance, with known sources of uncertainty visible to the decision-maker.