Transcription

The shape of a result

Model::transcribe() returns a Transcription:

$result = $model->transcribe('episode.wav');

$result->text();       // string — the full transcript
$result->segments();   // list<array{start: float, end: float, text: string}>
$result->count();      // int — number of segments
$result->duration();   // float — end of the last segment, in seconds

Segment offsets are seconds (floats). The concatenated segment texts equal text() modulo whitespace, so you can store segments and derive the transcript, or vice versa.

The segment row shape is deliberately identical to Displace\AI\Contracts\Transcriber’s documented return — a contracts adapter is two lines:

public function transcribe(string $audioPath, array $options = []): array
{
    $t = $this->model->transcribe($audioPath, $options);
    return ['text' => $t->text(), 'segments' => $t->segments()];
}

Options

$model->transcribe('interview.wav', [
    'language'  => 'de',    // ISO 639-1 hint; omit for auto-detect
    'translate' => true,    // translate to English (multilingual models)
    'threads'   => 4,       // pin the decoder thread count
]);

Unknown keys are ignored (forward compatibility); present-but-wrong types throw with the key named.

Deployment notes

• A loaded model is resident memory (75MB–500MB depending on size). The FPM guidance from ext-infer applies verbatim: load in CLI tools, queue workers, and daemons — not per-FPM-worker.
• transcribe() is synchronous and CPU-bound; budget roughly real-time × 0.1–0.5 on modern cores with tiny/base models.
• One Model handle is safe to share across threads: each call builds its own whisper state and no mutable state is shared.

The pipeline this feeds

Transcribe → chunk (ai-toolkit’s SentenceChunker fits transcripts well) → embed (ext-infer) → index (ext-turbovec): searchable audio archives, entirely on your hardware.