Speech-to-text Transcription
Speech-to-Text Transcription Batch Multilingual
Multilingual batch transcription with automatic language detection, speaker diarization, emotion and accent detection, and PII/PHI tagging.
POST
/
api
/
velma-2-stt-batch
Transcribe audio file with automatic language detection
curl --request POST \
--url https://platform.modulate.ai/api/velma-2-stt-batch \
--header 'Content-Type: multipart/form-data' \
--header 'X-API-Key: <api-key>' \
--form upload_file=@example-file \
--form medical_domain=false \
--form speaker_diarization=true \
--form emotion_signal=false \
--form accent_signal=false \
--form deepfake_signal=false \
--form pii_phi_tagging=false \
--form 'language=<string>' \
--form 'config=<string>;type=application/json'import requests
url = "https://platform.modulate.ai/api/velma-2-stt-batch"
files = { "upload_file": ("example-file", open("example-file", "rb")) }
files["config"] = (None, "<string>", "application/json")
payload = {
"medical_domain": "false",
"speaker_diarization": "true",
"emotion_signal": "false",
"accent_signal": "false",
"deepfake_signal": "false",
"pii_phi_tagging": "false",
"language": "<string>"
}
headers = {"X-API-Key": "<api-key>"}
response = requests.post(url, data=payload, files=files, headers=headers)
print(response.text)const form = new FormData();
form.append('upload_file', '<string>');
form.append('medical_domain', 'false');
form.append('speaker_diarization', 'true');
form.append('emotion_signal', 'false');
form.append('accent_signal', 'false');
form.append('deepfake_signal', 'false');
form.append('pii_phi_tagging', 'false');
form.append('language', '<string>');
form.append('config', '<string>');
const options = {method: 'POST', headers: {'X-API-Key': '<api-key>'}};
options.body = form;
fetch('https://platform.modulate.ai/api/velma-2-stt-batch', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://platform.modulate.ai/api/velma-2-stt-batch",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--",
CURLOPT_HTTPHEADER => [
"Content-Type: multipart/form-data",
"X-API-Key: <api-key>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://platform.modulate.ai/api/velma-2-stt-batch"
payload := strings.NewReader("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("X-API-Key", "<api-key>")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://platform.modulate.ai/api/velma-2-stt-batch")
.header("X-API-Key", "<api-key>")
.body("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--")
.asString();require 'uri'
require 'net/http'
url = URI("https://platform.modulate.ai/api/velma-2-stt-batch")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'
request.body = "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--"
response = http.request(request)
puts response.read_body{
"text": "Hello, how are you? Bonjour, ça va?",
"duration_ms": 5000,
"utterances": [
{
"utterance_uuid": "e5f6a7b8-c9d0-1234-efab-345678901234",
"text": "Hello, how are you?",
"start_ms": 0,
"duration_ms": 2000,
"speaker": 1,
"language": "en",
"emotion": "Neutral",
"accent": "American",
"deepfake_score": null
},
{
"utterance_uuid": "f6a7b8c9-d0e1-2345-fabc-456789012345",
"text": "Bonjour, ça va?",
"start_ms": 2500,
"duration_ms": 2500,
"speaker": 2,
"language": "fr",
"emotion": "Happy",
"accent": "British",
"deepfake_score": null
}
]
}Authorizations
API key used for authentication and usage tracking.
Body
multipart/form-data
Audio file to transcribe. Supported formats: AAC, AIFF, FLAC, MP3, MP4, MOV, OGG, Opus, WAV, WebM. Maximum file size: 100MB. Empty files are rejected.
When enabled, English audio is transcribed for medical dictation: misheard clinical terms (drug names, conditions, procedures) are corrected with a medical language model, and an opening or ending one transcriber dropped (patient name, chart number, date of birth) is recovered. Adds some latency. Other languages are transcribed as standard. When disabled or omitted, the standard transcription is returned.
Speaker diarization identifies different speakers in the audio. When enabled, each utterance includes a speaker identifier (e.g., 1, 2).
Emotion detection for each utterance. When enabled, each utterance includes an emotion signal detected from the speaker's voice.
Accent detection for each utterance. When enabled, each utterance includes an accent signal detected from the speaker's voice.
Synthetic voice (deepfake) detection for each utterance. When enabled, each utterance includes a deepfake_score indicating the likelihood that the speech is AI-generated. The score ranges from 0.0 (likely natural) to 1.0 (likely synthetic).
PII/PHI tagging in utterance text. When enabled, personally identifiable information and personal health information are wrapped with appropriate tags in the transcription text.
Optional language hint as a case-insensitive ISO 639-1 code (e.g. "en", "fr"). BCP 47 region/script subtags (e.g. "en-US") are accepted; only the primary language subtag is used. When omitted, the language is detected automatically for each utterance.
Pattern:
^[A-Za-z]{2,3}([-_][A-Za-z0-9]+)*$Optional JSON-encoded STT configuration. A field that has a
matching top-level form parameter overrides it; an omitted
field falls back to the form parameter. Supply custom_terms
here, e.g.
config={"custom_terms":["Modulate",{"term":"Velma","pronunciations":["VEL-muh"]}]}.
Response
Transcription completed successfully
The complete transcribed text from the audio file, containing all utterances concatenated together. This provides a full transcript of the audio content. Always present; may be an empty string when no speech was recognized.
Example:
"Hello everyone. Welcome to the meeting."
The total duration of the processed audio in milliseconds. This value represents the actual audio duration and is used for usage tracking and billing purposes.
Required range:
x >= 0Example:
45000
Array of individual utterances detected in the audio, ordered by start time. Each utterance represents a continuous segment of speech, potentially from a specific speaker if diarization is enabled. Always present; may be an empty array when no speech was recognized.
Show child attributes
Show child attributes
Transcribe audio file with automatic language detection
curl --request POST \
--url https://platform.modulate.ai/api/velma-2-stt-batch \
--header 'Content-Type: multipart/form-data' \
--header 'X-API-Key: <api-key>' \
--form upload_file=@example-file \
--form medical_domain=false \
--form speaker_diarization=true \
--form emotion_signal=false \
--form accent_signal=false \
--form deepfake_signal=false \
--form pii_phi_tagging=false \
--form 'language=<string>' \
--form 'config=<string>;type=application/json'import requests
url = "https://platform.modulate.ai/api/velma-2-stt-batch"
files = { "upload_file": ("example-file", open("example-file", "rb")) }
files["config"] = (None, "<string>", "application/json")
payload = {
"medical_domain": "false",
"speaker_diarization": "true",
"emotion_signal": "false",
"accent_signal": "false",
"deepfake_signal": "false",
"pii_phi_tagging": "false",
"language": "<string>"
}
headers = {"X-API-Key": "<api-key>"}
response = requests.post(url, data=payload, files=files, headers=headers)
print(response.text)const form = new FormData();
form.append('upload_file', '<string>');
form.append('medical_domain', 'false');
form.append('speaker_diarization', 'true');
form.append('emotion_signal', 'false');
form.append('accent_signal', 'false');
form.append('deepfake_signal', 'false');
form.append('pii_phi_tagging', 'false');
form.append('language', '<string>');
form.append('config', '<string>');
const options = {method: 'POST', headers: {'X-API-Key': '<api-key>'}};
options.body = form;
fetch('https://platform.modulate.ai/api/velma-2-stt-batch', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://platform.modulate.ai/api/velma-2-stt-batch",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--",
CURLOPT_HTTPHEADER => [
"Content-Type: multipart/form-data",
"X-API-Key: <api-key>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://platform.modulate.ai/api/velma-2-stt-batch"
payload := strings.NewReader("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("X-API-Key", "<api-key>")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://platform.modulate.ai/api/velma-2-stt-batch")
.header("X-API-Key", "<api-key>")
.body("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--")
.asString();require 'uri'
require 'net/http'
url = URI("https://platform.modulate.ai/api/velma-2-stt-batch")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'
request.body = "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"upload_file\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"medical_domain\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"speaker_diarization\"\r\n\r\ntrue\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"emotion_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"accent_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"deepfake_signal\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"pii_phi_tagging\"\r\n\r\nfalse\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"language\"\r\n\r\n<string>\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"config\"\r\nContent-Type: application/json\r\n\r\n<string>\r\n-----011000010111000001101001--"
response = http.request(request)
puts response.read_body{
"text": "Hello, how are you? Bonjour, ça va?",
"duration_ms": 5000,
"utterances": [
{
"utterance_uuid": "e5f6a7b8-c9d0-1234-efab-345678901234",
"text": "Hello, how are you?",
"start_ms": 0,
"duration_ms": 2000,
"speaker": 1,
"language": "en",
"emotion": "Neutral",
"accent": "American",
"deepfake_score": null
},
{
"utterance_uuid": "f6a7b8c9-d0e1-2345-fabc-456789012345",
"text": "Bonjour, ça va?",
"start_ms": 2500,
"duration_ms": 2500,
"speaker": 2,
"language": "fr",
"emotion": "Happy",
"accent": "British",
"deepfake_score": null
}
]
}