Dia TTS

Dia TTS TTS

A 1.6B-parameter model purpose-built for generating natural multi-speaker dialogue, not just single-voice narration.

ምዝገባ 5,000 ካራቴግራም

SSML tags ሒዝካ ጽሑፍካ ሒዝካ ንምውሳድ:

<speak><prosody rate="slow">Slow speech</prosody></speak>

ርኢቶታት እቲ ዝተመርጸ ሞዴል ዝፈልጦ — ጠቅልል ንኸውዕሎ ኣብ ጽሑፍካ ኣብ ዝግበር ቦታ:

እዚ ሞዴል'ዚ ጽሑፍ ቀሊል ይንብብ፣ ከምኡ'ውን ኣብ መስመር ዝርከብ ቴግታት ይቕረ ይበሃል። ን tag-based emotion፣ ናብ ሞዴል ስነ-ኣእምሮኣዊ ከም Orpheus ወይ Bark ምቕያር

ድምጺ ተለፎን (ቓል = ድምጺ)

-12 +12
0.5x 2.0x
ነጻ ምስ Piper, VITS, MeloTTS
እቲ ዝተፈጠረ ድምጺ እዚኣ ይርከብ። ሓደ ሞዴል ምረጽ፣ ጽሑፍ ኣትሒዝካ፣ ንተፈጥሮ ጠቅልል።
ድምጺ ተኸፊሉ
0:00
ድምጺ መዝጊብ .srt መዝገብ 24 ሰዓታት
ነጻ ደረጃ: ንባዕልኻ ንምጥቃም. ውልቀ-መዚ ውልቀ-መዚ ካብ $5/month
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ብዛዕባ Dia TTS

Dia by Nari Labs is a 1.6-billion-parameter text-to-speech model designed from the ground up for dialogue rather than monologue. It generates conversations between two speakers with realistic turn-taking, prosody, and emotional expression, producing audio that sounds like a real exchange instead of two voices read separately. Architecturally it pairs an autoregressive transformer with the Descript Audio Codec (DAC) for waveform generation. Dia is a strong fit for podcast-style content, scripted audiobook dialogue, and conversational scenes, and is released under Apache 2.0. Generations are heavier than single-voice models, so it favors quality over raw speed.

ምርኣይ: Podcasts, audiobook dialogues, conversational content

ርአ Dia TTS ቃላት

ኣብ ሓደ ገጽ

መተግበሪያ
Nari Labs
ውልቀ-መዚ
Apache 2.0
ቍጽሪ
standard
ፍጥነት
medium
ድምጺ
ኣይ
ቋንቋ
English
ቍጽሪ ኣርእስቲ
800

Dia TTS ቃላት

Speaker 1

English
ቍጽሪ Neutral

Speaker 2

English
ቍጽሪ Neutral

Dia TTS ሕቶታት ዝንበረሉ

Multi-speaker dialogue. Unlike most TTS models that read one voice at a time, Dia generates a two-speaker conversation with natural turn-taking, prosody, and emotion in a single pass — ideal for podcasts and scripted scenes.

It is a 1.6-billion-parameter model from Nari Labs, built on an autoregressive transformer with the Descript Audio Codec for audio generation.

On TTS.ai, Dia is configured for English. Its strength is dialogue generation rather than broad multilingual coverage.
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