Creating Voice Models

Learn how to create custom voice models with Fish Audio

Overview

Create custom voice models to generate consistent, high-quality speech. You can create models through our web interface or programmatically via API.

Web Interface

The easiest way to create a voice model:

1. Go to Fish Audio

   Visit fish.audio and log in

2. Navigate to Models

   Click on “Models” in your dashboard

3. Click Create Model

   Select “Create New Model”

4. Upload Your Audio

   Add 1 or more voice samples (at least 10 seconds each)

5. Configure Settings

   Choose privacy settings and training options

6. Start Training

   Click “Create” and wait for processing

Using the API

Using the SDK

Create models with the Python or JavaScript SDK:

Python

First, install the SDK:

pip install fish-audio-sdk

Then create a model:

from fish_audio_sdk import Session

# Initialize session with your API key
session = Session("your_api_key")

# Create the model
model = session.create_model(
    title="My Voice Model",
    description="Custom voice for storytelling",
    voices=[
        voice_file1.read(),
        voice_file2.read()
    ],
    cover_image=image_file.read()  # Optional
)

print(f"Model created: {model.id}")

JavaScript

First, install the SDK:

npm install fish-audio

Then create a model:

import { FishAudioClient } from "fish-audio";
import { createReadStream } from "fs";

const fishAudio = new FishAudioClient({ apiKey: process.env.FISH_API_KEY });

const title = "My Voice Model";
const audioFile1 = createReadStream("sample1.mp3");
// Optionally add more samples:
// const audioFile2 = createReadStream("sample2.wav");
const coverImageFile = createReadStream("cover.png"); // optional

try {
  const response = await fishAudio.voices.ivc.create({
    title,
    voices: [audioFile1],
    cover_image: coverImageFile,
    description: "Custom voice for storytelling",
    visibility: "private",
  });

  console.log("Voice created:", {
    id: response._id,
    title: response.title,
    state: response.state,
  });
} catch (err) {
  console.error("Create voice request failed:", err);
}

Direct API

Create models directly using the REST API:

Python

import requests

response = requests.post(
    "https://api.fish.audio/model",
    files=[
        ("voices", open("sample1.mp3", "rb")),
        ("voices", open("sample2.wav", "rb"))
    ],
    data=[
        ("title", "My Voice Model"),
        ("description", "Custom voice model"),
        ("visibility", "private"),
        ("type", "tts"),
        ("train_mode", "fast"),
        ("enhance_audio_quality", "true")
    ],
    headers={
        "Authorization": "Bearer YOUR_API_KEY"
    }
)

result = response.json()
print(f"Model ID: {result['id']}")

JavaScript

import { readFile } from "fs/promises";

const form = new FormData();
form.append("title", "My Voice Model");
form.append("description", "Custom voice model");
form.append("visibility", "private");
form.append("type", "tts");
form.append("train_mode", "fast");
form.append("enhance_audio_quality", "true");

const v1 = await readFile("sample1.mp3");
const v2 = await readFile("sample2.wav");
form.append("voices", new File([v1], "sample1.mp3"));
form.append("voices", new File([v2], "sample2.wav"));

const res = await fetch("https://api.fish.audio/model", {
  method: "POST",
  headers: { Authorization: "Bearer <YOUR_API_KEY>" },
  body: form,
});

const result = await res.json();
console.log("Model ID:", result.id);

Model Settings

Required Parameters

Parameter	Description	Type	Options
title	Name of your model	string	Any text
voices	Audio samples	Array<File>	.mp3, .wav, .m4a, .opus
type*	Model type	enum<string>	tts
train_mode*	Model train mode, fast means model instantly available after creation	enum<string>	fast

*Automatically set by Python and JavaScript SDKs

Optional Parameters

Parameter	Description	Type	Options
visibility	Who can use your model	enum<string>	private, public, unlist default: public
description	Model description	string	Any text
cover_image	Model cover image, required if the model is public	File	.jpg, .png
texts	Transcripts of audio samples	Array<string>	Must match number of audio files
tags	Tags for your model	string[]	Any text
enhance_audio_quality	Remove background noise	boolean	true, false default: false

For detailed explanations view our API reference.

Audio Requirements

Quality Guidelines

Minimum Requirements:

• At least 1 audio sample
• 10+ seconds per sample

Best Practices:

• Use multiple diverse samples
• 1 consistent speaker throughout
• Include different emotions and tones
• Record in a quiet environment
• Maintain steady volume

Adding Transcripts

Including text transcripts improves model quality:

Python

response = requests.post(
    "https://api.fish.audio/model",
    files=[
        ("voices", open("hello.mp3", "rb")),
        ("voices", open("world.wav", "rb"))
    ],
    data=[
        ("title", "Enhanced Model"),
        ("texts", "Hello, this is my first recording."),
        ("texts", "Welcome to the world of AI voices."),
        # ... other parameters
    ],
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

JavaScript

import { FishAudioClient } from "fish-audio";
import { createReadStream } from "fs";

const fishAudio = new FishAudioClient({ apiKey: process.env.FISH_API_KEY });

const response = await fishAudio.voices.ivc.create({
  title: "Enhanced Model",
  voices: [
    createReadStream("hello.mp3"),
    createReadStream("world.wav"),
  ],
  texts: [
    "Hello, this is my first recording.",
    "Welcome to the world of AI voices.",
  ],
  // other optional fields:
  // visibility: "private",
  // enhance_audio_quality: true,
});

console.log("Model ID:", response._id);

Text transcripts must match the exact number of audio files. If you provide 3 audio files, you must provide exactly 3 text transcripts.

Using Your Model

Once training is complete:

Python

# Generate speech with your model
response = requests.post(
    "https://api.fish.audio/v1/tts",
    json={
        "text": "Hello from my custom voice!",
        "model_id": model_id,
        "format": "mp3"
    },
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

# Save the audio
with open("output.mp3", "wb") as f:
    f.write(response.content)

JavaScript

import { FishAudioClient } from "fish-audio";
import { writeFile } from "fs/promises";

const fishAudio = new FishAudioClient({ apiKey: process.env.FISH_API_KEY });

const audio = await fishAudio.textToSpeech.convert({
  text: "Hello from my custom voice!",
  model_id: "your_model_id_here",
  format: "mp3",
});

const buffer = Buffer.from(await new Response(audio).arrayBuffer());
await writeFile("output.mp3", buffer);
console.log("✓ Audio saved to output.mp3");

Troubleshooting

Common Issues

Model training fails:

• Check audio quality and format
• Ensure single speaker in all samples
• Verify files are not corrupted

Poor voice quality:

• Add more diverse audio samples
• Enable audio enhancement
• Use higher quality recording

Best Practices

1. Start Simple: Begin with 2-3 samples in fast mode to test
2. Iterate: Refine with more samples and quality mode
3. Document: Keep track of which samples work best
4. Test Thoroughly: Try different texts and emotions
5. Privacy First: Keep personal models private

Support

Need help creating models?

• API Documentation: Full API Reference
• Discord Community: Join our Discord
• Email Support: [e-mail]