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natural text to speech for youtube videos

keep the narration steady from the opening line to the final cut so the video feels easier to watch

narration built for watch time

narration built for watch time

narration built for watch time

create a voice that carries the video 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

faceless videos
generate narration for faceless youtube channels covering top 10 lists and story videos.
video explainers
an ai voice for youtube tutorials, how-tos, screen recordings and product breakdowns.
shorts
voice overs for youtube shorts covering hooks, quick stories and fast edits.
review videos
generate voice overs for gadget reviews, app reviews and unboxings using silk api.

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 youtube voice overs in three steps

generate production-ready youtube voice overs in three steps

generate production-ready youtube 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.

youtube-videos

youtube videos across languages and accents

youtube videos across languages and accents

youtube-videos

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

youtube videos across languages and accents

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

where ai youtube narration falls short

where ai youtube narration falls short

where ai youtube narration falls short

a voice can be clear and still make the video feel harder to watch

problemwhat goes wronghow silk helps
sounds roboticthe voice stays too even for a video with cuts, examples, and changes in pace.silk follows delivery cues, so the narration can speed up for quick parts and slow down when the point needs space.
no natural pausestransitions, jokes, and section breaks run into each other.silk reads punctuation and line breaks as part of the performance, not just the text.
misreads nameschannel names, product names, and mixed-language words come out wrong.silk text to speech handles multilingual and code-mixed speech closer to how people actually say it.

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

yes. you can use silk's text to speech to turn a youtube script into narration for explainers, faceless videos, reviews, tutorials, and shorts. open the playground or use the silk api when the channel has a repeatable production workflow.
yes, text to speech can be used in monetized youtube videos when the video is original and adds real value for viewers. silk's text to speech gives the narration a natural, realistic voice, so the audio feels made for the video instead of read by a default ai narrator.
youtubers use text to speech tools like silk to turn scripts into narration for faceless channels, tutorials, product reviews, and short-form clips. silk gives them 12 voice presets, 22 indian languages, and wav or mp3 output for their editor.
robotic narration sounds too even. silk lets you shape the voice around the video, with clearer pauses for scene changes, stronger emphasis on key lines, and a more natural pace across the script.
yes, you can use text to speech for faceless youtube videos. silk can generate narration for list videos, explainers, product breakdowns, story videos, and review channels where the voice needs to carry the video.
yes, silk text to speech handles 22 indian languages and code-mixed speech closer to how people actually say it. that helps with channel names, product terms, and hindi-english lines.

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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2026 - rumik

join us

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

company

contact

contact

careers

careers

research

research

ira

ira

privacy policy

privacy policy

terms

terms

api

playground

playground

text to speech

text to speech

api keys

api keys

agents

agents

pricing

pricing

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docs

support

support

community

X

linkedin

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