Which API should I use? - Modulate

Modulate’s models are grouped into families by the kind of output they produce. Within a family, endpoints differ by language coverage, latency, and whether they take a file or a live stream. Each capability page below carries the full parameter, response, and audio format detail for its endpoints.

Model families

Family	Model	Output
Transcription	Multilingual Transcription	A transcript with per-utterance timing, speaker labels, and optional emotion, accent, deepfake, and PII/PHI signals. Batch and streaming.
	English Fast Transcription	An English transcript, with speaker turns when diarization is enabled. Batch and streaming.
	Multilingual Fast Transcription	A transcript, its duration, and its language. No metadata. Batch and streaming, though only batch reports the language.
Detection	Deepfake Detection	A `synthetic`, `non-synthetic`, or `no-content` verdict per frame, with confidence. Batch and streaming.
	Emotion Detection	A whole-file emotion label plus a per-window time series. Batch.
	Accent Detection	A whole-file accent label plus a per-window time series. Batch.
	Music & Speech Detection	Music and speech probabilities per 192 ms frame, plus clip totals. Batch and streaming.
	AI Music Detection	A clip verdict on AI-generated music, plus per-window vocal and instrumental scores. Batch and streaming.
	Language Detection	The spoken language with a confidence score, across 100 languages. Batch.
	Audio Event Detection	A probability for each non-speech sound event detected, from a vocabulary of 42. Batch.
Redaction	PII/PHI Redaction	A redacted transcript plus audio with the sensitive ranges silenced. Batch and streaming.
Triage	Velma Triage	Behaviors, conversation type, participant roles, topics, sentiment, a summary, and a diarized transcript. Batch and streaming.

No Detection model returns a transcript.

Endpoints that overlap

Three models return a transcript

Multilingual Transcription, PII/PHI Redaction, and Velma Triage all return a transcript. Pairing any of the last two with a transcription call returns the same text twice.

Requirement	Endpoint that covers it
A redacted transcript and audio with the sensitive ranges silenced	PII/PHI Redaction. A separate transcription call returns the same text.
Behaviors, topics, and sentiment across a conversation	Velma Triage. The diarized transcript comes back as `clips`.

Four signals have two paths

Each is available as a flag on Multilingual Transcription, attached per utterance, or as a dedicated endpoint that produces no transcript. English Fast and Multilingual Fast Transcription carry none of them.

Signal	Multilingual Transcription flag	Dedicated endpoint	What the dedicated endpoint adds
Deepfake	`deepfake_signal=true`, one score per utterance	Deepfake Detection	Frame-level verdicts, explicit `no-content` for silence, and verdicts on live audio without a transcript
Emotion	`emotion_signal=true`, one label per utterance	Emotion Detection	A whole-file label and a per-window time series, without a transcript
Accent	`accent_signal=true`, one label per utterance	Accent Detection	A whole-file label and a per-window time series, without a transcript
PII/PHI	`pii_phi_tagging=true`, spans tagged in the transcript text	PII/PHI Redaction	Silenced audio, not only tagged text

Common scenarios

Goal	Endpoint
Recorded English calls, high volume	English Fast Transcription (batch). Bound parallel requests with a semaphore to stay inside the concurrency cap.
Recorded calls in mixed or non-English languages, transcript only	Multilingual Fast Transcription (batch). Pass `language` when it is known.
Live non-English captions, minimum latency	Multilingual Fast Transcription (streaming), for the 25 European languages it covers. The language is identified automatically, and `detect_language=true` reports it per utterance. Outside those 25, use Multilingual Transcription (streaming).
Captions, or search that seeks into the audio	English Fast Transcription (batch) with `time_stamps=true`. Returns a start time, end time, and alignment confidence per word, in seconds from the start of the file.
Live English captions timed to the word	English Fast Transcription (streaming) with `time_stamps=true`. Each final utterance carries a start and duration per word, in milliseconds from the start of the stream.
Meeting transcription with speakers and emotion	Multilingual Transcription (batch) with `speaker_diarization=true` and `emotion_signal=true`.
Recorded English clinical dictation	English Fast Transcription (batch) or Multilingual Transcription (batch) with `medical_domain=true`. Corrects drug names, conditions, and procedures.
Live captions with speaker labels or non-English audio	Multilingual Transcription (streaming).
Voice agent input, minimum latency	English Fast Transcription (streaming) with `endpointing=true`. Replace the displayed partial on each message rather than appending.
Live English captions that attribute turns to speakers	English Fast Transcription (streaming) with `diarize=true` and `endpointing=true`. Check `speakers_capped` before trusting the labels past ten speakers.
Screening a submitted clip for AI-generated voice	Deepfake Detection (batch).
Anti-spoofing during a live voice-authentication flow	Deepfake Detection (streaming). Frame verdicts arrive during the call.
A compliance recording that must be shareable	PII/PHI Redaction (batch). Returns the silenced MP3 and the tagged transcript together.
Routing audio by spoken language	Language Detection (batch). Read `predicted_language_code`; low `confidence` means no commitment.
Processing only speech from a live stream	Music & Speech Detection (streaming). Route on the frame classification.
Screening uploaded tracks for AI-generated music	AI Music Detection (batch). The clip `primary_verdict` is more accurate than the per-window scores.
Identifying non-speech sounds in a clip	Audio Event Detection (batch). Entries are independent probabilities, so threshold each event you care about; an absent key means not confidently detected, not absent from the audio.
Fraud or compliance review on recorded calls	Velma Triage (batch) with a detection package.
Live monitoring for escalation or churn	Velma Triage (streaming). `behavior_detection` events arrive during the call.