AI Music Detection Batch

POST

api

velma-2-ai-music-detection-batch

Detect AI-generated music in an audio file

curl --request POST \
  --url https://platform.modulate.ai/api/velma-2-ai-music-detection-batch \
  --header 'Content-Type: multipart/form-data' \
  --header 'X-API-Key: <api-key>' \
  --form upload_file=@example-file

import requests

url = "https://platform.modulate.ai/api/velma-2-ai-music-detection-batch"

files = { "upload_file": ("example-file", open("example-file", "rb")) }
headers = {"X-API-Key": "<api-key>"}

response = requests.post(url, files=files, headers=headers)

print(response.text)

const form = new FormData();
form.append('upload_file', '<string>');

const options = {method: 'POST', headers: {'X-API-Key': '<api-key>'}};

options.body = form;

fetch('https://platform.modulate.ai/api/velma-2-ai-music-detection-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-ai-music-detection-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--",
  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-ai-music-detection-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--")

	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-ai-music-detection-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--")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://platform.modulate.ai/api/velma-2-ai-music-detection-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--"

response = http.request(request)
puts response.read_body

{
  "filename": "my_audio.mp3",
  "duration_s": 89.28,
  "primary_verdict": "ai-vocal-music",
  "vocal_percentage": 87.5,
  "vocal_ai_percentage": 56.5,
  "vocal_ai_confidence": 0.96,
  "instrumental_percentage": 64.3,
  "instrumental_ai_percentage": 10.5,
  "instrumental_ai_confidence": 0.95,
  "silence_percentage": 3.51,
  "windows": [
    {
      "start_time_ms": 0,
      "end_time_ms": 4000,
      "vocal_percentage": 100,
      "vocal_ai_probability": 0.97,
      "vocal_ai_confidence": 0.97,
      "instrumental_percentage": 79,
      "instrumental_ai_probability": 0.42,
      "instrumental_ai_confidence": 0.16,
      "silence_percentage": 0
    },
    {
      "start_time_ms": 4000,
      "end_time_ms": 8000,
      "vocal_percentage": 0,
      "vocal_ai_probability": null,
      "vocal_ai_confidence": null,
      "instrumental_percentage": 82,
      "instrumental_ai_probability": 0.88,
      "instrumental_ai_confidence": 0.76,
      "silence_percentage": 18
    }
  ],
  "latency_ms": 1333
}

Authorizations

X-API-Key

string

header

required

API key used for authentication and usage tracking.

Body

multipart/form-data

upload_file

file

required

Audio file to analyse. Must be non-empty. Supported formats: .3g2, .3ga, .3gp, .3gpp, .8svx, .aa3, .aac, .ac3, .act, .adts, .aif, .aifc, .aiff, .alac, .amb, .amr, .ape, .asf, .at3, .au, .avi, .avr, .awb, .bwf, .c2, .caf, .dss, .dts, .dtshd, .eac3, .ec3, .f4a, .f4b, .flac, .flv, .gsm, .iff, .m2a, .m2ts, .m4a, .m4b, .m4r, .m4v, .mka, .mkv, .mlp, .mmf, .mov, .mp+, .mp1, .mp2, .mp3, .mp4, .mpa, .mpc, .mpeg, .mpg, .mpga, .mpp, .mts, .mxf, .nist, .oga, .ogg, .ogx, .oma, .omg, .opus, .paf, .pvf, .qcp, .ra, .rf64, .rka, .rm, .rmvb, .sf, .shn, .snd, .sph, .svx, .tak, .thd, .ts, .tta, .vob, .voc, .vqf, .w64, .wav, .wave, .weba, .webm, .wma, .wmv, .wv. Maximum file size: 100 MB.

Response

Detection completed successfully.

filename

string

required

Name of the submitted audio file. Empty string if no filename was provided in the upload.

Example:

"my_audio.mp3"

duration_s

number<double>

required

Total duration of the analysed audio in seconds.

Required range: x >= 0

Example:

89.28

primary_verdict

enum<string>

required

Clip-level classification:

ai-vocal-music - AI-generated music with a detected synthetic voice (covers AI songs and AI synthetic vocal tracks).
ai-instrumental - AI-generated instrumental music with no detectable synthetic voice.
not-ai-music - the clip does not appear to contain AI-generated music.

Available options:

ai-vocal-music,

ai-instrumental,

not-ai-music

Example:

"ai-vocal-music"

vocal_percentage

number<double>

required

Clip-level average percentage of the audio that contains vocal content, averaged across all windows.

Required range: 0 <= x <= 100

Example:

87.5

vocal_ai_percentage

number<double>

required

Clip-level AI-vocal score, on a 0-100 scale: each scored window's probability-weighted duration as a percentage of the full clip duration. Windows without enough vocal content to score contribute zero to the numerator but their duration still counts toward the total, so a clip that is mostly instrumental with only a brief, confidently-synthetic vocal patch does not read as overwhelmingly AI-vocal.

Required range: 0 <= x <= 100

Example:

56.5

vocal_ai_confidence

number<double>

required

Average confidence across all windows that were scored for AI-generated vocals. Not diluted by windows without enough vocal content to score.

Required range: 0 <= x <= 1

Example:

0.89

instrumental_percentage

number<double>

required

Clip-level average percentage of the audio that contains instrumental music content, averaged across all windows.

Required range: 0 <= x <= 100

Example:

64.3

instrumental_ai_percentage

number<double>

required

Clip-level AI-instrumental score, on a 0-100 scale: the duration-weighted average of each scored window's AI-instrumental probability. Windows that are mostly silence do not contribute.

Required range: 0 <= x <= 100

Example:

10.5

instrumental_ai_confidence

number<double>

required

Average confidence across all windows that were scored for AI-generated instrumental content. Zero if no window was scored.

Required range: 0 <= x <= 1

Example:

0.95

silence_percentage

number<double>

required

Clip-level average percentage of the audio that contains neither vocal nor instrumental content, averaged across all windows.

Required range: 0 <= x <= 100

Example:

3.51

windows

object[]

required

Per-window breakdown of detection results.

Show child attributes

latency_ms

number<double>

required

End-to-end inference time in milliseconds.

Required range: x >= 0

Example:

1333

Detect AI-generated music in an audio file

curl --request POST \
  --url https://platform.modulate.ai/api/velma-2-ai-music-detection-batch \
  --header 'Content-Type: multipart/form-data' \
  --header 'X-API-Key: <api-key>' \
  --form upload_file=@example-file

import requests

url = "https://platform.modulate.ai/api/velma-2-ai-music-detection-batch"

files = { "upload_file": ("example-file", open("example-file", "rb")) }
headers = {"X-API-Key": "<api-key>"}

response = requests.post(url, files=files, headers=headers)

print(response.text)

const form = new FormData();
form.append('upload_file', '<string>');

const options = {method: 'POST', headers: {'X-API-Key': '<api-key>'}};

options.body = form;

fetch('https://platform.modulate.ai/api/velma-2-ai-music-detection-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-ai-music-detection-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--",
  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-ai-music-detection-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--")

	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-ai-music-detection-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--")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://platform.modulate.ai/api/velma-2-ai-music-detection-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--"

response = http.request(request)
puts response.read_body

{
  "filename": "my_audio.mp3",
  "duration_s": 89.28,
  "primary_verdict": "ai-vocal-music",
  "vocal_percentage": 87.5,
  "vocal_ai_percentage": 56.5,
  "vocal_ai_confidence": 0.96,
  "instrumental_percentage": 64.3,
  "instrumental_ai_percentage": 10.5,
  "instrumental_ai_confidence": 0.95,
  "silence_percentage": 3.51,
  "windows": [
    {
      "start_time_ms": 0,
      "end_time_ms": 4000,
      "vocal_percentage": 100,
      "vocal_ai_probability": 0.97,
      "vocal_ai_confidence": 0.97,
      "instrumental_percentage": 79,
      "instrumental_ai_probability": 0.42,
      "instrumental_ai_confidence": 0.16,
      "silence_percentage": 0
    },
    {
      "start_time_ms": 4000,
      "end_time_ms": 8000,
      "vocal_percentage": 0,
      "vocal_ai_probability": null,
      "vocal_ai_confidence": null,
      "instrumental_percentage": 82,
      "instrumental_ai_probability": 0.88,
      "instrumental_ai_confidence": 0.76,
      "silence_percentage": 18
    }
  ],
  "latency_ms": 1333
}

Velma

Speech-to-text Transcription

Deepfake Detection

Emotion Detection

Accent Detection

PII/PHI Redaction

Music Detection