ttsds/voicecraft:d693bf62 – Run with an API on Replicate

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ttsds /voicecraft:d693bf62

Playground API

Input

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text

*string

Shift + Return to add a new line

With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.

Text to synthesize

speaker_reference

*file

Reference audio file

text_reference

*string

Shift + Return to add a new line

and keeping eternity before the eyes, though much.and keeping eternity before the eyes, though much.

Transcript of reference audio

version

string

Version of the model to use

Default: "giga330m"

Run this model in Node.js with one line of code:

npx create-replicate --model=ttsds/voicecraft

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run ttsds/voicecraft using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ttsds/voicecraft:d693bf62054c6bd92898ea6b644317a9bb912881fb2c37a0fad4ce26b59f0539",
  {
    input: {
      text: "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.",
      version: "giga330m",
      text_reference: "and keeping eternity before the eyes, though much.",
      speaker_reference: "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav"
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run ttsds/voicecraft using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ttsds/voicecraft:d693bf62054c6bd92898ea6b644317a9bb912881fb2c37a0fad4ce26b59f0539",
    input={
        "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.",
        "version": "giga330m",
        "text_reference": "and keeping eternity before the eyes, though much.",
        "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav"
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run ttsds/voicecraft using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "ttsds/voicecraft:d693bf62054c6bd92898ea6b644317a9bb912881fb2c37a0fad4ce26b59f0539",
    "input": {
      "text": "With tenure, Suzie\'d have all the more leisure for yachting, but her publications are no good.",
      "version": "giga330m",
      "text_reference": "and keeping eternity before the eyes, though much.",
      "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

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{
  "completed_at": "2025-02-26T12:46:00.898854Z",
  "created_at": "2025-02-26T12:42:07.745000Z",
  "data_removed": false,
  "error": null,
  "id": "b2js7ntw05rj00cn893t3w0nhc",
  "input": {
    "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.",
    "version": "giga330m",
    "text_reference": "and keeping eternity before the eyes, though much.",
    "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav"
  },
  "logs": "INFO     Setting up corpus information...\nINFO     Loading corpus from source files...\n   1%                                      1/100  [ 0:00:01 < -:--:-- , ? it/s ]\nINFO     Found 1 speaker across 1 file, average number of utterances per\nspeaker: 1.0\nINFO     Initializing multiprocessing jobs...\nINFO     Normalizing text...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]\nINFO     Generating MFCCs...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:12 < 0:00:00 , ? it/s ]\nINFO     Calculating CMVN...\nINFO     Generating final features...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]\nINFO     Creating corpus split...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]\nINFO     Compiling training graphs...\nINFO     Performing first-pass alignment...\nINFO     Generating alignments...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]\nINFO     Calculating fMLLR for speaker adaptation...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]\nINFO     Performing second-pass alignment...\nINFO     Generating alignments...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]\nINFO     Collecting phone and word alignments from alignment lattices...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:02 < 0:00:00 , ? it/s ]\nWARNING  Alignment analysis not available without using postgresql\nINFO     Exporting alignment TextGrids to /tmp/tmphk_hfkzo/mfa_alignments...\n 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:00 < 0:00:00 , ? it/s ]\nINFO     Finished exporting TextGrids to /tmp/tmphk_hfkzo/mfa_alignments!\nINFO     Done! Everything took 70.744 seconds",
  "metrics": {
    "predict_time": 79.023730294,
    "total_time": 233.153854
  },
  "output": "https://replicate.delivery/yhqm/9aeIbkwlkhyILiz23FSX1Y14TfppQboQueLep4g6wAvgwvMRB/output.wav",
  "started_at": "2025-02-26T12:44:41.875123Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/yswh-fbsvlojvo62m7ag6gnctefdjutazdy2e4a4snprch22cokks7m3a",
    "get": "https://api.replicate.com/v1/predictions/b2js7ntw05rj00cn893t3w0nhc",
    "cancel": "https://api.replicate.com/v1/predictions/b2js7ntw05rj00cn893t3w0nhc/cancel"
  },
  "version": "d693bf62054c6bd92898ea6b644317a9bb912881fb2c37a0fad4ce26b59f0539"
}

Generated in

79.0 seconds

Tweak it ShareReport

INFO     Setting up corpus information...
INFO     Loading corpus from source files...
   1%                                      1/100  [ 0:00:01 < -:--:-- , ? it/s ]
INFO     Found 1 speaker across 1 file, average number of utterances per
speaker: 1.0
INFO     Initializing multiprocessing jobs...
INFO     Normalizing text...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]
INFO     Generating MFCCs...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:12 < 0:00:00 , ? it/s ]
INFO     Calculating CMVN...
INFO     Generating final features...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]
INFO     Creating corpus split...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]
INFO     Compiling training graphs...
INFO     Performing first-pass alignment...
INFO     Generating alignments...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]
INFO     Calculating fMLLR for speaker adaptation...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]
INFO     Performing second-pass alignment...
INFO     Generating alignments...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:01 < 0:00:00 , ? it/s ]
INFO     Collecting phone and word alignments from alignment lattices...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:02 < 0:00:00 , ? it/s ]
WARNING  Alignment analysis not available without using postgresql
INFO     Exporting alignment TextGrids to /tmp/tmphk_hfkzo/mfa_alignments...
 100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1/1  [ 0:00:00 < 0:00:00 , ? it/s ]
INFO     Finished exporting TextGrids to /tmp/tmphk_hfkzo/mfa_alignments!
INFO     Done! Everything took 70.744 seconds