Every sound has
something to say.

Tink learns the hums, clicks, and sighs one person can still make, then says what each one means out loud, in their own banked voice.

Tink sits between a person and the room. It listens for the sounds they can still make, matches each one to a phrase they taught it, and says that phrase, so nobody has to guess.

For the person

Their words. Their voice.

Each phrase plays back as a recording of them saying it, banked while they still could.

For caregivers

Less guessing. Faster answers.

Urgent sounds raise an alarm until someone answers, and you can type a reply that Tink says aloud.

For privacy

Nothing leaves the laptop.

Audio, video, and the sound model stay on the device. No account, no cloud service.

How it works

Five recordings, then it listens.

  1. 01

    Teach a sound

    Record a hum, click, sigh, or vowel about five times and type what it means.

  2. 02

    Make the sound

    Tink compares it with that person’s sounds and shows how sure it is, including “I don’t know.”

  3. 03

    Hear the meaning

    Tink plays the phrase in their banked voice, or reads it aloud if none is banked yet.

Live app

Try it below.

This is the real app, not a mockup. It runs on your laptop: start the server, teach at least two sounds, press Listen, and make one of them. The first run downloads the voc2vec model.

Tink

speaks for them, in their voice
voc2vec
Ready
Teach Tink two sounds.
  1. Teach two sounds0 of 2 taught
  2. Press Listenand make one of them
  3. Tink says itin the language you pick

Press space to listen. Tink stops by itself when the sound ends.

Answer back

Heard today

this session

    Nothing heard yet.

    What leaves this laptop

    Audio and video never leave this laptop.

    Privacy

    Their voice stays theirs.

    Microphone audio
    Stays on this laptop
    Banked voice recordings
    Stays on this laptop
    Webcam video
    Read in the browser, never uploaded
    AI services
    None. Nothing is sent out.
    Under the hood

    Built for sounds that aren’t words.

    1. 01SoundA clip from the mic
    2. 02voc2vecA model trained on non-verbal sounds
    3. 03BayesA confidence that can say “unknown”
    4. 04VoiceThe phrase, out loud

    Measured On real sounds from 8 minimally speaking people (ReCANVo), Tink picks the right meaning 27% of the time, against 19% by chance. Those were spontaneous sounds, not deliberate signals, so it is a hard test. Read the method