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natural text to speech for voice overs

give each line a voice that fits the scene and lands the way the script needs

voice overs built for range

voice overs built for range

voice overs built for range

move from calm to urgent to cinematic with 12 voice presets and delivery control

type ‹ to insert emotion tags

built for real production work

built for real production work

built for real production work

video ads
generate voice overs for paid ads and launch videos with silk's text to speech api.
brand videos
an ai voice for the company film, campaign videos and the founder stories.
documentaries
narration for short films, docs and video essays that sounds like a real narrator.
phone systems
text to speech for the greetings, menus and hold messages on your support line.

silk keeps the voice intact even through language changes

silk keeps the voice intact even through language changes

silk keeps the voice intact even through language changes

narrator
description: a male 40s british voice, low pitch, gravelly timbre, slow pacing, neutral, formal register, like a dramatic narrator. text: the door creaked open. nobody was there. and yet, something watched.
0:00 / 0:00
podcast host
description: a female 30s hindi voice, normal pitch, smooth timbre, conversational pacing, energetic, casual register, like a podcast host. text: आज का episode थोड़ा अलग है। एक minute के लिए सीधा बैठ जाओ।
0:00 / 0:00
support
description: a female 30s indian voice, normal pitch, warm timbre, conversational pacing, neutral, neutral register, like a customer support agent. text: मैं आपकी help के लिए यहाँ हूँ। एक minute, मैं check करती हूँ।
0:00 / 0:00
streamer
description: a male 20s american voice, high pitch, smooth timbre, very fast pacing, excited, casual register, like a streamer reacting live. text: oh my god, did you see that play? that was insane!
0:00 / 0:00

generate production-ready voice overs in three steps

generate production-ready voice overs in three steps

generate production-ready voice overs in three steps

call silk from your product workflow, or open the playground to hear the voice before shipping

silk api

silk api

silk api

  1. Create your key

  1. Create your key

  1. Create your key

grab a key from api keys in the playground. name it whatever you like.

  1. choose a voice model

  1. choose a voice model

  1. choose a model

mulberry-1.6 covers all 22 languages. muga adds tone tags for hindi-english lines.

  1. call the api

  1. call the api

send the model and text, get a wav back. add audio_format for other formats.

from rumikai import Rumik

client = Rumik()  # reads RUMIK_API_KEY
audio = client.speech.create(
    text="Hello, what can I do for you?",
    model="mulberry-1.6",
    description="professional, Indian English accent, steady pace",
)
audio.save("speech.wav")
import requests

url = "[https://silk-api.rumik.ai/v1/tts](https://silk-api.rumik.ai/v1/tts)"

payload = {
    "model": "mulberry-1.6",
    "text": "Hello, what can I do for you?", 
    "description": "professional, British accent, steady pace", 
    "speaker": "aisha",
}
headers = {"Authorization": "Bearer <token>"}

response = requests.post(url, json=payload, headers=headers)

with open("speech.wav", "wb") as f:
    f.write(response.content)
import requests

url = "[https://silk-api.rumik.ai/v1/tts](https://silk-api.rumik.ai/v1/tts)"

payload = {
    "model": "mulberry-1.6",
    "text": "Hello, what can I do for you?", 
    "description": "professional, British accent, steady pace", 
    "speaker": "aisha",
}
headers = {"Authorization": "Bearer <token>"}

response = requests.post(url, json=payload, headers=headers)

with open("speech.wav", "wb") as f:
    f.write(response.content)

silk playground

silk playground

silk playground

  1. paste your text

    enter the english sentence you want to hear. keep punctuation, numbers, and mixed-language phrases exactly as you want them spoken.

  2. choose a model

    select the silk model for english, then adjust the available settings for the voice and delivery you need.

  3. generate the audio

    listen to the result, refine the text or settings when needed, and download the audio when the line is ready.

ai-voice-over

voice overs across languages and accents

voice overs across languages and accents

ai-voice-over

build speech for 22 indian languages, english accents, and regional delivery from the same silk stack

voice overs across languages and accents

build speech for 22 indian languages, english accents, and regional delivery from the same silk stack

where ai voice overs fall short

where ai voice overs fall short

where ai voice overs fall short

the voice can sound real and still miss the moment the line was written for

problemwhat goes wronghow silk helps
no voice directionthe voice says the line, but it does not feel like it belongs to the scene.rumik silk carries the voice direction with the text, so the delivery starts with the mood you want.
weak line stressthe important word passes by too quickly, and the line loses its punch.silk follows punctuation and delivery cues to place weight where the script needs it.
one-note deliverythe ad, the brand film, and the phone greeting all start to feel like the same read.silk text to speech gives each job its own voice direction, tone, and timing instead of one voice style everywhere.

meet the teams already speaking through silk

curvet put mulberry and muga directly inside its ai workflow canvas. within two days, teams generated voices across education, design, crm and enterprise workflows.

100 + hours in 2 days

curvet ai

snaptv uses silk to give a voice to bite-sized lessons made for how india learns, quickly, on mobile, in simple hindi and easy english.

snap tv

Image (9) (no background)

jee concepts are difficult enough. monk learning uses silk to turn dense explanations into clear, natural voice for aspirants preparing every day.

monk learning

meet the teams already speaking through silk

meet the teams already speaking through silk

curvet put mulberry and muga directly inside its ai workflow canvas. within two days, teams generated voices across education, design, crm and enterprise workflows.

curvet put mulberry and muga directly inside its ai workflow canvas. within two days, teams generated voices across education, design, crm and enterprise workflows.

100 + hours in 2 days

100 + hours in 2 days

curvet ai

snaptv uses silk to give a voice to bite-sized lessons made for how india learns, quickly, on mobile, in simple hindi and easy english.

snaptv uses silk to give a voice to bite-sized lessons made for how india learns, quickly, on mobile, in simple hindi and easy english.

snap tv

Image (9) (no background)

jee concepts are difficult enough. monk learning uses silk to turn dense explanations into clear, natural voice for aspirants preparing every day.

jee concepts are difficult enough. monk learning uses silk to turn dense explanations into clear, natural voice for aspirants preparing every day.

monk learning

frequently asked questions

frequently asked questions

frequently asked questions

text to speech is used in voice overs when you need spoken audio from a written script. silk helps you generate that for video ads, brand films, documentaries, product videos, phone greetings, and support line messages from the same speech api.
open the silk playground, enter the line you want to hear, choose the voice direction, and generate the audio. if the voice over needs to run inside your product or content workflow, call the same silk speech stack through the api.
a robotic voice over usually comes from flat pacing and weak emphasis. silk lets you guide the tone, pause around important lines, and put weight on the words that should land.
yes, silk's text to speech can be used to generate ai voice overs for commercial videos, including paid ads, launch videos, company films, and product explainers.
yes, silk's text to speech models can pronounce brand names and product names when they are written clearly in the script. for unusual spellings, add a simple pronunciation cue or test a short line in the playground before generating the full voice over.
yes, you can use the silk api to generate voice overs from your own app, editor, cms, or production workflow. it is useful when you need to create voice overs for many videos, campaigns, languages, or versions without doing each one by hand.

explore more voice use cases

where teams use english voice

explore more voice use cases

start building with rumik's tts api

start building with rumik's tts api

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we are a close-knit group of researchers, engineers, and designers working on the hardest problems in ai.

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