Announcing our Series A Funding

Announcing our Series A Funding

Young Voices

One hundred and forty six voices are tagged young, 63 percent of the catalog, across every accent and all twelve recommended languages. Unlike tone, age is a real tagged field rather than an inference.

VOICES FOR THIS USE CASE

Jennajenna
FemaleYoungAmerican
Best for EnglishUse voice
Paripari
FemaleYoungIndian
Best for HindiUse voice
Ishaanishaan
MaleYoungIndian
Best for HindiUse voice
Pratikpratik
MaleYoungIndian
Best for HindiUse voice
Sahanasahana
FemaleYoungIndian
Best for HindiUse voice
Junejune
FemaleYoungKorean
Best for KoreanUse voice

One hundred and forty six voices

Young is the larger of the two age groups, covering 63 percent of the catalog and spanning every accent and all twelve recommended languages. Unlike most attributes on these pages, age is a genuine tagged field rather than an inference, so this list is filtered rather than judged.

Where younger voices fit

Social media and gaming are the usual contexts. Four voices carry the social media tag and fourteen the character tag, and there is meaningful overlap with the young group. For gaming specifically, WebSocket streaming allows dialogue to be generated during play rather than pre-rendered.

Age is not adjustable

There is no age parameter, so a voice cannot be made to sound younger after generation. This is a casting decision. Given the size of the group, the practical approach is to narrow by accent and language first, then audition within what remains.

A caveat on tagging

The underlying data used several spellings for this attribute, including young, Young and young adult, which have been normalised into one value here. If you query the API directly rather than using this catalog, expect to handle that variation yourself.

SPECIFICATION

Sample rate

44.1 kHz native, resampled to 8 kHz for telephony

Latency

~200 ms to first byte (p50, warm region)

Output formats

ulaw, alaw, PCM 16-bit, WAV, MP3

Streaming transports

WebSocket, HTTP chunked transfer

Speed range

0.5× – 2.0×, set per request

Explore Voice Similar to

Young Voices

Mature Voices

Eighty six voices are tagged mature, and twenty also carry the narrative tag. That overlap is the usual starting point for audiobooks and documentary work, where consistency shows over hours rather than seconds.

Energetic Voices

Speed is the reliable lever here, not casting. Settings between 1.2 and 1.4 lift almost any voice in the catalog, though longer sentences start to blur past roughly 1.5.

Cheerful Voices

Only six voices in the catalog show cheerful or positive markers, the thinnest tone signal available. Speed slightly above 1.0 lifts almost any voice, which is the more dependable route.

Female Voices

One hundred and one female voices, spanning six accent groups and all twelve recommended languages. At that scale accent and language usually constrain casting more than gender does.

AI Voices for YouTube Voiceover

Short form rewards pace, and speed adjusts up to 2.0. Scripts change after the edit, so generating line by line means retiming a section costs one line rather than the whole track.

AI Voices for Gaming & Character Voices

Pre-rendering every branch means shipping every branch. WebSocket streaming lets dialogue generate during play instead, so a conversation tree costs what players actually hear rather than what they might.

Expressive Voices

There is no emotion parameter, so range comes from the voice and from how the line is written. Fourteen voices carry the character tag, and those have the widest delivery available.

Male Voices

One hundred and twenty male voices across every accent group and all twelve recommended languages. Most carry an Indic recommendation, which is unusual in catalogs that treat Indian languages as an afterthought.

Deep Voices

Worth saying plainly: nothing in the catalog records pitch, so these six were chosen by ear rather than filtered. There is no pitch control either, so depth is a casting decision.

Authoritative Voices

Slowing down reads as more authoritative than speeding up. A setting near 0.9 does more than any voice choice, and short declarative sentences carry more weight than qualified ones.

Mature Voices

Eighty six voices are tagged mature, and twenty also carry the narrative tag. That overlap is the usual starting point for audiobooks and documentary work, where consistency shows over hours rather than seconds.

Energetic Voices

Speed is the reliable lever here, not casting. Settings between 1.2 and 1.4 lift almost any voice in the catalog, though longer sentences start to blur past roughly 1.5.

Cheerful Voices

Only six voices in the catalog show cheerful or positive markers, the thinnest tone signal available. Speed slightly above 1.0 lifts almost any voice, which is the more dependable route.

Female Voices

One hundred and one female voices, spanning six accent groups and all twelve recommended languages. At that scale accent and language usually constrain casting more than gender does.

AI Voices for YouTube Voiceover

Short form rewards pace, and speed adjusts up to 2.0. Scripts change after the edit, so generating line by line means retiming a section costs one line rather than the whole track.

AI Voices for Gaming & Character Voices

Pre-rendering every branch means shipping every branch. WebSocket streaming lets dialogue generate during play instead, so a conversation tree costs what players actually hear rather than what they might.

Expressive Voices

There is no emotion parameter, so range comes from the voice and from how the line is written. Fourteen voices carry the character tag, and those have the widest delivery available.

Male Voices

One hundred and twenty male voices across every accent group and all twelve recommended languages. Most carry an Indic recommendation, which is unusual in catalogs that treat Indian languages as an afterthought.

FAQs

One hundred and forty six of two hundred and thirty two, making it the larger of the two age groups. They span every accent and all twelve recommended languages. Note that age is a property of the voice, not a setting, so a voice cannot be made to sound younger after the fact.