AI Music Creative Mediation Available in French

Suno

Suno Inc. (Cambridge, Massachusetts) — Launched 2023

At a glance: Suno is an AI music generator that turns a few words or a text into a complete song — lyrics, melody, vocals, and instrumentation. With over 2.4 million active users in 2026, it is the reference tool in this space. Its relevance for mental health lies in a pioneering clinical use: an occupational therapist in forensic psychiatry uses it as a creative mediation tool in sessions, with promising clinical outcomes on emotional regulation, verbal expression, and identity building.

Identity

Publisher: Suno Inc. (Cambridge, MA, USA)

Launch: 2023 (beta), public availability 2024

Type: AI music generator (text → audio)

Valuation: ~$500M (Series B, 2024)

Pricing: Free (10 songs/day) / Pro (~500 songs/month) / Premier (unlimited)

Languages: Multilingual (generates in the language of the input text)

Access: Web (suno.com), mobile app

Usage rights: Commercial use on paid plans only

What Suno Does (in plain terms)

Suno generates a complete song — lyrics, melody, sung vocals, and instrumental arrangement — from a simple text or a few keywords. The user needs no musical skills whatsoever.

Inputs

Keywords Text / lyrics Musical style (genre) Reference audio

Outputs

Complete song (1–4 min) AI-generated vocals Instrumental arrangement Cover image

Two main modes: “Describe Your Song” (a few words suffice, Suno generates lyrics and music) and “Custom” (the user writes their own lyrics and selects the genre). In both cases, Suno produces multiple variations that the user can listen to, compare, and refine.

The result is immediate (30 to 60 seconds) and requires no knowledge of music theory, composition, or production. This radical accessibility is what makes it a potential mediation tool.

Documented Mental Health Uses

Unlike ChatGPT, Suno is not spontaneously used by patients for emotional support. Its use in mental health is emerging and clinician-led, primarily driven by practitioners integrating it into creative mediation frameworks. The scientific literature on Suno specifically is still very limited, but two types of data exist.

Clinical protocol: “6 words → song”

Gaëlle Charlot, an occupational therapist at the SMPR Bordeaux-Gradignan (forensic psychiatry unit, France), has developed a structured protocol for using Suno in therapy sessions:

  1. The patient chooses six words that are meaningful to them
  2. Suno generates lyrics from those words; the patient selects the version that resonates
  3. The patient chooses a musical style (rap, folk, metal, classical, techno…)
  4. Suno produces multiple versions of the song
  5. Shared listening, ranking, elaboration — the same text “sounds” different across styles

This protocol is used with incarcerated patients presenting varied profiles: schizophrenia with negative symptoms, poly-substance use disorders, personality disorders, cognitive impairments. It requires no reading or writing skills from the patient.

Observed clinical effects

  • Emotional differentiation: the same text set to different styles helps patients discover that their words “sound” differently depending on context — work on perception and tone that transfers to social interactions.
  • Bodily engagement: psychotic patients with negative symptoms were observed following the music rhythmically, expressing a physical preference between versions.
  • Identity building: a patient with severe poly-substance use disorder began identifying as a “music creator,” taking care of their appearance, and experiencing pleasure outside of substance use.
  • Post-session autonomy: some patients continue using Suno independently after discharge, integrating the tool into their daily life — a transfer of therapeutic gains that is rare in these populations.
  • Frustration tolerance: the gap between what one imagines and what Suno produces creates a tolerable frustration, conducive to working on reality testing.

Academic research

  • Dartmouth College (2025): the HeartDJ project (master’s thesis) uses Suno to generate personalized music in real time from heart rate variability (HRV) data, for well-being interventions.
  • ArXiv (2025): a study compares perceptions of Suno-generated music and human-composed music for emotional regulation applications. Results suggest that framing (knowing whether it’s AI or not) influences perceived authenticity and effectiveness.
  • Frontiers in Digital Health (2025): a literature review on integrating music therapy, brain entrainment, and AI into a unified therapeutic paradigm.

Level of evidence: The uses described here are primarily based on qualitative clinical observations (practitioner testimony, self-report questionnaires from 2 patients). No randomized controlled trial on the use of Suno in therapy exists yet. These data are exploratory and promising, not conclusive.

The “Non-Perceptible Third”

In occupational therapy, mediation is the third element in the therapeutic relationship: clay, wicker, drawing serve as concrete supports that mediate the exchange between patient and clinician.

Gaëlle Charlot proposes the concept of “non-perceptible third” to describe what generative AI does within this framework: a third element that is neither a physical material nor a conventional piece of software, but an unpredictable semantic transformation. We don’t know exactly how Suno interprets the patient’s words, and it is precisely this opacity that creates a therapeutic space: the result surprises, displaces, and opens up dialogue.

This concept echoes Winnicott’s transitional object (neither fully internal nor fully external) and Pease’s therapeutic computational creativity FR (2022) — the idea that AI’s generativity can be therapeutically productive precisely because it escapes the control of both the patient and the clinician.

Risks and Limitations

Copyright issues

Suno faces lawsuits from Sony, Universal, and Warner for unauthorized use of copyrighted music in its training data. The legal status of AI-generated music remains uncertain.

Cost for patients

The free tier is very limited (10 songs/day). For regular independent use, the paid plan represents a cost that vulnerable populations may struggle to afford.

Platform dependency

Creations are hosted on Suno’s servers. If the platform changes its terms, shuts down, or deletes content, patients lose their creations — which can have a significant emotional impact.

Unpredictable generated content

Suno can generate unexpected lyrics or themes from the patient’s keywords. In a clinical setting, professional supervision is essential to manage these potential surprises.

Level of evidence

No controlled trial, very few empirical studies. The reported clinical outcomes are exclusively qualitative and not generalizable at this stage.

Correctional setting access

Using Suno requires internet access, which is extremely restricted in correctional facilities. The tool can only be used under direct clinician supervision, limiting independent practice.

Our Analysis

Suno represents a different case from ChatGPT. It is not a tool that patients spontaneously use to talk about their problems — it is a creative mediator integrated into a therapeutic framework by a professional. The distinction is fundamental.

What makes Suno clinically interesting is the combination of three properties: radical accessibility (no prior skills required), immediacy of result (a complete song in 30 seconds), and controlled variation (the same text in multiple styles). These three elements allow reaching patients who are typically failed by traditional mediations: cognitive impairments, lack of education, frustration intolerance.

The testimony of the poly-substance use disorder patient who discovers an identity as a “creator” is particularly striking. This is a shift from pleasure through substance to pleasure through creation — which, in the addiction field, constitutes a significant marker of recovery.

Caution is warranted, however: we are at the case report stage, not at evidence level. Gaëlle Charlot’s protocol is led by an experienced practitioner, within a specific institutional setting. Its transfer to other contexts will require formalization and rigorous evaluation. But the signal is interesting enough to merit attention from clinicians and researchers in digital art therapy.

References

Charlot, G. (2024). L’ergothérapie : vers une approche moderne et numérique de la pratique en psychiatrie. ResearchGate.

Zubala, A. et al. (2025). Art psychotherapy meets creative AI: An integrative review. The Arts in Psychotherapy.

Pease, A. (2022). Therapeutic Computational Creativity. In Computational Creativity, Springer.

HeartDJ (2025). Music Recommendation and Generation through Biofeedback. Dartmouth College, Master’s Thesis.

Sharman, L. & Dingle, G. (2014). Extreme metal music and anger processing. Frontiers in Human Neuroscience, 8, 272.

Frontiers in Digital Health (2025). Advancing personalized digital therapeutics: integrating music therapy, brainwave entrainment methods, and AI-driven biofeedback.

Last updated: February 2026

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