> ## Documentation Index
> Fetch the complete documentation index at: https://kb.vinfer.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Multilingual Voice Support: 25+ Languages and Dialects

> VInfer Neuron supports 25+ Indian and global languages with dialect-level understanding, code-switching, and noisy call-center audio robustness.

Language is where most voice AI systems fall apart in the Indian market. A model trained on clean, studio-quality recordings of standard Hindi does not hold up against a customer calling from a tier-3 city on a 2G connection, mixing Rajasthani-inflected Hindi with English product names. VInfer built Neuron's language engine from the ground up for India's actual linguistic reality — not a translation layer on top of a Western model, but a voice-native system trained on the diversity, noise, and code-switching patterns of real Indian customer calls.

## Supported Indian Languages

Neuron covers India's major scheduled languages plus regionally spoken variants that are critical for high-volume calling in specific geographies:

<CardGroup cols={2}>
  <Card title="Hindi (hi-IN)" icon="microphone">
    Standard Hindi with coverage of Hindustani variants. Handles Devanagari-script literacy levels, formal and informal registers, and heavy English code-switching.
  </Card>

  <Card title="Tamil (ta-IN)" icon="microphone">
    Tamil with dialect sensitivity across Tamil Nadu and Sri Lankan Tamil communities. Handles both formal literary Tamil and spoken colloquial forms.
  </Card>

  <Card title="Telugu (te-IN)" icon="microphone">
    Telugu with coverage of Andhra Pradesh and Telangana dialectal variation — distinct enough in practice to matter for agent performance.
  </Card>

  <Card title="Marathi (mr-IN)" icon="microphone">
    Marathi including regional variations across Vidarbha, Marathwada, and coastal Maharashtra. Handles English and Hindi borrowings common in urban Marathi speech.
  </Card>

  <Card title="Kannada (kn-IN)" icon="microphone">
    Kannada across its northern and southern dialects, with robustness for Bangalore's heavily code-switched urban variety.
  </Card>

  <Card title="Bengali (bn-IN)" icon="microphone">
    Bengali with coverage for both West Bengal and Bangladesh-origin speakers. Handles the significant phonological differences between Kolkata and Dhaka varieties.
  </Card>

  <Card title="Gujarati (gu-IN)" icon="microphone">
    Gujarati with dialect sensitivity across Saurashtra, Kutchi, and urban Ahmedabad varieties. Strong English code-switching support for business communities.
  </Card>

  <Card title="Punjabi (pa-IN)" icon="microphone">
    Punjabi (Gurmukhi) including coverage for Malwi, Doabi, and Majhi dialectal regions. Also handles Punjabi-Hindi-English trilingual code-switching common in urban callers.
  </Card>

  <Card title="Malayalam (ml-IN)" icon="microphone">
    Malayalam with sensitivity to the strong regional dialectal variation across central and northern Kerala. Handles English-heavy professional speech common among Kerala's large educated workforce.
  </Card>

  <Card title="Odia (or-IN)" icon="microphone">
    Odia with coverage for standard and coastal varieties. Handles Hindi and English borrowings common in urban Bhubaneswar and Cuttack speech.
  </Card>

  <Card title="Bhojpuri" icon="microphone">
    Bhojpuri spoken across eastern Uttar Pradesh and Bihar. Critical for rural financial services and FMCG outreach at scale in this belt.
  </Card>

  <Card title="Rajasthani & Haryanvi" icon="microphone">
    Regional spoken variants of western Hindi — frequently used for rural collections and government scheme outreach in Rajasthan and Haryana.
  </Card>
</CardGroup>

<Info>
  Additional Indian language and dialect variants are added regularly. Contact your VInfer account team for the current full list or to request prioritization of a language your campaigns require.
</Info>

## Supported English Variants

<CardGroup cols={2}>
  <Card title="Indian English (en-IN)" icon="globe">
    The primary English variant for India-based campaigns. Trained on Indian-accented speech across major metro and tier-2 cities. Handles Indian phonological patterns, rhythm, and intonation that differ significantly from Western English models.
  </Card>

  <Card title="British English (en-GB)" icon="globe">
    Standard British English for UK-facing campaigns or Indian customers with British English exposure.
  </Card>

  <Card title="US English (en-US)" icon="globe">
    Standard American English for North American campaigns or global customer segments.
  </Card>
</CardGroup>

<Tip>
  Use `en-IN` for any English-language campaign targeting customers in India. Neuron's `en-IN` model significantly outperforms `en-US` for Indian-accented speech — connect rates and comprehension scores are consistently higher. Reserve `en-US` for campaigns explicitly targeting a North American customer base.
</Tip>

## Language Code Reference

Use these BCP-47 codes when setting the `language` parameter in your agent configuration or campaign API calls:

| Language  | Region/Variant | BCP-47 Code |
| --------- | -------------- | ----------- |
| Hindi     | India          | `hi-IN`     |
| Tamil     | India          | `ta-IN`     |
| Telugu    | India          | `te-IN`     |
| Marathi   | India          | `mr-IN`     |
| Kannada   | India          | `kn-IN`     |
| Bengali   | India          | `bn-IN`     |
| Gujarati  | India          | `gu-IN`     |
| Punjabi   | India          | `pa-IN`     |
| Malayalam | India          | `ml-IN`     |
| Odia      | India          | `or-IN`     |
| English   | India          | `en-IN`     |
| English   | United States  | `en-US`     |
| English   | United Kingdom | `en-GB`     |

<Note>
  Bhojpuri, Rajasthani, and Haryanvi are supported as acoustic models under the `hi-IN` language family. Contact your account team for the specific model variant identifiers for these languages.
</Note>

## Code-Switching

Code-switching — switching between two languages mid-sentence — is the norm for hundreds of millions of Indian speakers, not the exception. A customer might say: *"Bhai, mujhe is EMI ke baare mein koi issue nahi hai, but the amount looks wrong on my statement."*

Neuron handles this natively. It does not require the customer to stay in one language, and it does not lose conversational context when the language shifts. Specifically:

* **Mid-sentence switches** are processed as a unified utterance — Neuron understands the complete meaning across both languages
* **Domain vocabulary in English** (loan amount, EMI, statement, OTP, PIN) is recognized correctly even when embedded in a non-English sentence
* **Asymmetric switching** — where the customer speaks primarily in one language but Neuron responds in another based on your agent configuration — is fully supported
* **Script-to-language mismatch handling** — if a customer responds in a language other than the agent's primary language, Neuron detects this and adapts rather than failing

<Tabs>
  <Tab title="Hindi–English Example">
    **Customer:** "Mera loan ka due date kab hai? And can I pay online?"

    **Neuron processes:** Full meaning across both segments — due date query (Hindi) + payment channel query (English) — and responds to both in a single, natural turn.
  </Tab>

  <Tab title="Tamil–English Example">
    **Customer:** "Naan already payment panniten, but it's not reflecting in your system."

    **Neuron processes:** Past payment assertion (Tamil) + system reflection issue (English) — routes to the dispute branch of the conversation flow.
  </Tab>

  <Tab title="Gujarati–Hindi–English Example">
    **Customer:** "Mane koi problem nahi, bas mujhe ek week ka time chahiye, I'll pay by Friday."

    **Neuron processes:** Three-language utterance — positive intent with a time-bound commitment — and captures the callback/payment date for CRM logging.
  </Tab>
</Tabs>

## Acoustic Robustness

Indian call center audio presents challenges that break most voice AI systems. Neuron is specifically engineered to handle them:

<AccordionGroup>
  <Accordion title="Low-Bitrate and Compressed Audio">
    Neuron maintains high comprehension accuracy on 8kHz telephony audio — the standard for PSTN and many mobile networks in India — without requiring HD audio.
  </Accordion>

  <Accordion title="Background Noise">
    Training includes real-world call center recordings with typical background conditions: street noise, household sounds, overlapping conversations, and poor acoustic environments common in tier-2 and tier-3 locations.
  </Accordion>

  <Accordion title="Regional Accents">
    Each language model is trained on regionally diverse speaker pools. A `hi-IN` call from Bihar is not processed the same way as one from Delhi — the model accounts for phonological variation across geographies.
  </Accordion>

  <Accordion title="Varied Speech Rates">
    Neuron handles fast talkers, slow deliberate speakers, and the mid-call pace changes that happen when customers switch from casual to serious mode (or vice versa).
  </Accordion>

  <Accordion title="Telephony Artifacts">
    Echo, clipping, packet loss, and DTMF tones in the audio stream are handled gracefully — Neuron does not misinterpret these as speech or lose its place in the conversation.
  </Accordion>
</AccordionGroup>

## Setting Language in Your Campaign

Set the `language` parameter when creating a campaign via the API:

```bash theme={null}
curl -X POST https://api.vinfer.ai/v1/campaigns \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Tamil Nadu Collections — June",
    "script_id": "script_collections_ta_v1",
    "language": "ta-IN",
    "contacts": [...]
  }'
```

Or select the language in the dashboard when creating a new campaign under **Neuron → Campaigns → New Campaign → Language**.

<Warning>
  The language set on the campaign overrides the default language on the voice agent for that campaign run. Make sure your script content matches the language you configure — running a Hindi script with `ta-IN` set will produce degraded results.
</Warning>

## Next Steps

* [Configure your voice agent](/neuron/voice-agents) and set the language code
* [Launch a campaign](/neuron/campaigns) targeting a specific language segment
* [Set up integrations](/neuron/integrations) to receive call outcomes in your CRM