Mental health has a sound, and AI is beginning to hear and mix it. In the
voice and language, we find traces of affect, depression, and recovery that can open new pathways for scalable and personalised
care. Starting there, we will explore how speech-based digital psychology is expanding from diagnosis toward intervention: from
vocal and linguistic biomarkers of mental well-being to large language models that support rather than simply assess, reaching
to generative music systems that enable closed-loop personalised emotional regulation. This convergence of speech AI,
interventive language technology, and generative audio suggests a future in which intelligent systems can listen, understand,
and respond in psychologically meaningful ways. Realising that future, however, requires more than technical performance. It
demands beyond clinical relevance reliability, safety, explainability, and trust. I will discuss the promise, route, and
responsibility of building AI that does not merely analyse the mind, but helps care and deejay for it.