> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pyai.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Language support
> Which languages PyAI supports on Hear (STT), Cue, Omni, and Speak (TTS) today: what is GA and benchmarked, what is hint-accepted, and what is roadmap.
This page is the single source of truth for **which languages work on which
product today**. We publish what is GA and benchmarked, what is accepted but not
yet measured, and what is roadmap, so you can plan an integration without
guessing.
**Short version:** English is GA and benchmarked across every product. **Omni
is going multilingual**: agents can be configured for `fr`, `es`, `de`, and
`hi` end to end (recognition, reasoning, and voice), with per-language
availability being enabled in stages, French first, then Spanish, German, and
Hindi. For Hear/Cue, the `language` hint is accepted and forwarded to the
engine, but recognition accuracy for non-English is **not yet published**. For
a non-English voice pipeline outside Omni's supported set, the pattern is
**Cue (turn detection + your knowledge base) + your own LLM and TTS**.
## Status at a glance
| Product | English | Other languages | Native non-English voices |
| ------------------------------------------- | ---------------- | ---------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
| **Hear**, speech-to-text | GA · benchmarked | Accepted as a hint · accuracy not yet published | n/a |
| **Cue**, turn detection + KB grounding | GA · benchmarked | Accepted as a hint · accuracy not yet published | n/a (you bring TTS) |
| **Omni**, agentic voice (STT + brain + TTS) | GA · end-to-end | `fr` / `es` / `de` / `hi` end-to-end · staged rollout (FR first) | Via Omni sessions in those languages (incl. Hindi Standard/Natural tiers) |
| **Speak**, text-to-speech | GA | n/a | Not yet in the standalone catalog, English voices only (incl. Indian-English accents) |
**Legend.** *GA · benchmarked* = supported and we publish accuracy numbers.
*Accepted as a hint* = the `language` parameter is forwarded to the engine and
may work, but we make no published accuracy guarantee yet. *Roadmap* = planned,
not available today.
## Hear & Cue (speech-to-text)
The streaming endpoint (`GET /v1/audio/transcriptions/stream`) and the batch
endpoint (`POST /v1/transcription/jobs`) accept an optional `language` parameter:
```
GET /v1/audio/transcriptions/stream?model=pyai-hear&language=en&sample_rate=16000&encoding=pcm16
```
* `language` is an **ISO-639-1 hint** forwarded to the engine.
* It is **one hint per session**, there is **no mid-session auto-detect** and no
per-turn language switching today.
* **English** is the GA, benchmarked language. Published English accuracy:
**\~1.6% WER on clean audio** and **\~4.8% WER on an 8 kHz telephony/accented
corpus** (see [Benchmarks](https://pyai.com/benchmarks)).
* Other ISO-639-1 codes are **accepted** and forwarded, but we **do not yet
publish accuracy** for them. Treat non-English STT as unmeasured until the
numbers land on the benchmarks page.
The OpenAI-compatible synchronous endpoint (`POST /v1/audio/transcriptions`)
is **English-only** today: a non-English `language` there is rejected with
`400 unsupported_language` rather than forwarded, so a wrong-language request
fails loudly instead of silently returning a mis-transcribed transcript. The
hint behavior described above applies to the streaming endpoint and async
batch jobs. For an end-to-end non-English pipeline, use Omni.
### Indian languages & code-mixed speech
This is a frequent request, so we are explicit about it. Today PyAI does **not
publish** word-error-rate numbers for Hindi, Tamil, Telugu, Bengali, Marathi,
Kannada, Malayalam, Gujarati, or Punjabi, nor for **code-mixed Hinglish /
Tanglish** (Roman + native script mixed with English). The `language` hint will
accept these codes, but you should **not assume production accuracy** until we
publish measured results.
If your product depends on Indian-language or code-mixed transcription accuracy,
**validate on your own audio before committing.** Talk to us and we will run a
joint accuracy evaluation against your real call samples, that measurement is
the right go/no-go signal, not this page. The benchmark harness we use for this
lives in the repo at `evals/benchmarks/hear-multilingual.benchmark.json`.
## Omni (agentic voice)
Omni runs the full loop, speech-to-text, the brain, and text-to-speech, on the
PyAI engine, and it is **going multilingual**: `en` (default), `fr`, `es`,
`de`, and `hi`, end to end. Set the language once on the agent profile and
every call on that agent runs in it:
```bash theme={null}
curl https://api.pyai.com/v1/agents \
-H "Authorization: Bearer $PYAI_API_KEY" \
-d '{ "name": "Agente de Ventas", "language": "es" }'
```
* `language` is an **agent-level** setting (an agent is "a Spanish agent").
It can also be sent per session in the `configure` frame, which wins over
the profile (see the [Omni protocol reference](/realtime/omni-protocol)).
Absent or `null` means `en`, exactly the pre-multilingual behavior.
* **Availability is staged per language**: French first, then Spanish, German,
and Hindi. Configuring an agent for a language before its rollout reaches
your traffic degrades gracefully: the session falls back to English and the
call proceeds (the `configured` ack reports `language_active` and
`language_fallback: true`), and the call bills as what was actually served.
Ask us if you need early access.
* **Hindi has two voice tiers.** `standard` is included in the base Omni rate
and fits web and app experiences. `natural` is the telephony-premium tier
and bills a per-minute add-on on top of the base Omni minutes (see
[Pricing & metering](/pricing-and-metering)). Other languages are
single-tier today.
* Per-phone-number language mapping and automatic language detection are
fast-follows, not part of this rollout.
For a language outside this set, use the composable path:
1. **Cue**, stream call audio for turn detection (and optional knowledge-base
grounding) on `GET /v1/audio/transcriptions/stream`.
2. **Your LLM**, generate the reply from the Cue transcript + grounding.
3. **Your TTS**, synthesize the reply in the target language and play it back.
## Speak (text-to-speech)
The Speak catalog (`GET /v1/voices`) is **English voices only** today. This
includes several **Indian-English accent** voices (filter `?region=india`), but
those speak **English** (`language: "en"`), not Hindi/Tamil/etc.
There is **no native Indian-language (or other non-English) TTS** in the catalog
yet, and `POST /v1/audio/speech` has no `language` parameter. For non-English
speech output, **bring your own TTS** in the composable path above. Non-English
voices and non-English voice cloning are on the roadmap.
## How accuracy gets published
We gate engine quality in CI with an offline benchmark harness (`evals/`) and
publish the headline numbers on the [Benchmarks](https://pyai.com/benchmarks)
page. As languages are measured, their numbers appear there and this matrix is
updated. If you need a number that isn't published yet, ask, an unpublished
number means "not measured to our bar," not "hidden."
## See also
Feed live call audio into Hear / Cue streaming.
Connect, configure, and the live-vs-roadmap field table.
μ-law ↔ PCM16 at 8 kHz for phone legs.
Per-second billing and the rate card.