Japanese
TTS Voices
Japanese text-to-speech voices with natural pitch patterns
From text to talk.
Pick your path.
Call our TTS & STT endpoints directly, wire voice into LiveKit rooms with one plug-in, or spin up an AI assistant on a real phone number.
TTS & STT Endpoints
Production-grade streaming and batch TTS/STT. Low latency, 50+ languages, customizable voices, and SDKs for Node/Python/Browser.
- ›Streaming for live apps
- ›Multi-speaker diarization & punctuation
- ›SDKs, code samples, and latency benchmarks
Sends text to the TTS endpoint and saves the synthesized audio as an MP3 file.
LiveKit Plug-in
Plug our real-time speech pipeline into LiveKit rooms — transcribe live sessions, synthesize responses and stream audio back into the room.
- ›One-line install, example room demo
- ›WebRTC + server bridge patterns
- ›Works in browser & mobile
Connects to a LiveKit room and attaches real-time TTS/STT — transcribes audio in, synthesizes audio out.
AI-Assistants (Phone)
Deploy a phone-number based AI assistant in minutes — inbound/outbound calls, IVR, call recording, and DTMF support.
- ›Purchase & map a phone number
- ›Templates: Support Bot, Sales Assistant, Reminder Bot
- ›PSTN reliability & compliance tools
Creates an AI assistant bound to a phone number with inbound call handling, recording, and DTMF support.
Spanish voices
294TTS voicesEspañol
French voices
98TTS voicesFrançais
German voices
82TTS voicesDeutsch
Indonesian voices
31TTS voicesBahasa Indonesia
Italian voices
51TTS voicesItaliano
Japanese voices
85TTS voices日本語
Korean voices
171TTS voices한국어
Portuguese voices
277TTS voicesPortuguês
Russian voices
34TTS voicesРусский
Chinese voices
189TTS voices中文
Japanese phonology and prosody
Every mora gets its time
English is stress-timed[1]: stressed syllables recur at roughly even intervals while unstressed syllables collapse toward schwa. Japanese runs on a different clock: it is mora-timed[2], where each mora receives roughly equal duration. "Interesting" in casual English compresses to something like in-trst-ing[3]; a comparable Japanese word keeps every mora evenly spaced. A TTS system trained on English stress-timing imposes the wrong rhythmic skeleton on Japanese output. Producing natural mora-timed speech requires models that control sub-syllabic duration at inference, co-located with the audio pipeline so timing information survives intact.
Pitch accent carries meaning
English marks word identity through lexical stress[1]: louder, longer, higher-pitched syllables: as in REcord (noun) vs. reCORD (verb). Japanese replaces that mechanism with pitch accent[2]: meaning depends on where pitch falls across morae, not on loudness or duration. The triplet 箸 / 橋 / 端 (chopsticks / bridge / edge) differs primarily in pitch contour[3], not stress. An engine that maps English stress cues onto Japanese mispronounces words at the semantic level. Resolving pitch accent demands inference infrastructure built for prosodic control, not a chain of providers each adding latency.
Strict syllables, no clusters
English tolerates heavy consonant clusters[1]: "strengths" stacks multiple consonants around a single vowel. Japanese syllable structure is almost exclusively CV[2]: one consonant, one vowel, with only /N/ or a geminate allowed as a coda. When Japanese absorbs "strike," it becomes /sɯ.to.ɾa.i.kɯ/[3], padding each consonant with a vowel to maintain the CV pattern. TTS architectures built around English phonotactics produce illegal syllable shapes or unnatural epenthetic pauses. Accurate Japanese synthesis needs models that enforce CV constraints natively, with inference co-located alongside audio processing so syllable boundaries stay clean.