# Advanced Features
### :mag: Context Biasing (Hotwords)
You can boost recognition of important or uncommon phrases by specifying hotwords during the WebSocket request.
#### Using Hotwords
Define your hotwords as a JSON array. You can specifiy a higher "boosting score" if you would like to provide extra emphasis to longer phrases (recommended!). Currently, the default score applied is `1.5` which should be sufficient for single words.
hindi_hotwords = [
{ "phrase": "बोधी" },
{ "phrase": "स्पीच रिकग्निशन", "score": 2.5 }
]
Once you have defined your JSON array of hotwords, you can input it to the model while sending in the configuration
```python
await ws.send(
json.dumps(
{
"config": {
"sample_rate": 8000,
"transaction_id": str(uuid.uuid4()),
"model": "hi-banking-v2-8khz",
"hotwords": hindi_hotwords
}
}
)
)
```
#### Best Practices
| Best Practice | Description |
| -------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
| ✅ Use uncommon words | Target domain-specific or rare phrases like `"`बोधी स्पीच रिकग्निशन`"` |
| ✅ Use local script | Always write in Devanagari (e.g. बोधी, not `bodhi`) |
| ✅ Avoid punctuation | Remove quotes, commas, periods |
| ✅ Use higher scores for longer phrases | e.g. "बोधी स्पीच रिकग्निशन " -> 2.5 vs
"बोधी" -> 1.5
|
> Avoid copying hotwords from other providers without validation. Bodhi may already support commonly spoken Hindi words natively.
#### Warnings
* Avoid very short particles like `"का"`, `"की"`, `"ए"`, etc.
* Don’t boost every word in a sentence — only uncommon or error-prone segments.
* Phrases work better for commonly missed phrases, individual tokens are better for rare words.
* Avoid boosting words that already work as is.
***
### 🧠 Confidence Scoring
Bodhi returns both **segment-level** confidence for all finalized results. You can use this to decide whether to use the response or not. For instance, in extremely noisy surrounding, confidence thresholds can be used to reduce unintended transcriptions.
#### Segment Confidence
```json
{
"text": "मुझे जानकारी चाहिए",
"is_final": true,
"confidence": 0.79
}
```
#### Word-level Confidence
```json
{
"text": "मुझे जानकारी चाहिए",
"is_final": true,
"confidence": 0.79,
"words": [
{ "word": "मुझे", "confidence": 0.82 },
{ "word": "जानकारी", "confidence": 0.91 },
{ "word": "चाहिए", "confidence": 0.72 }
]
}
```
#### Recommended Usage
| Use Case | Strategy |
| ----------------------------------- | -------------------------------------------------------------------------------------------------------- |
| Filter out weak segments | Depending on language the confidence threshold can be somewhere in the range of 0.65 - 0.75. |
| Tune per language and per use case | Call center vs dictation use cases need different thresholds. This threshold can also vary per language. |
***
### 🧹 Partial Result Exclusion
To avoid reacting to incomplete guesses, use the `exclude_partial` flag in the configuration. The client will only receive complete transcripts.
```json
{
"config": {
"sample_rate": sample_rate,
"transaction_id": str(uuid.uuid4()),
"model": "hi-banking-v2-8khz",
"exclude_partial":True
}
}
```
***
### 🔢 Parse Numbers into Numerals
Bodhi supports converting spoken number words into actual digits using the `parse_number` flag in the WebSocket config.
This is useful when transcribing sentences that include monetary values, phone numbers, addresses, or quantities — especially for use cases like banking, insurance, and logistics.
#### ✅ How to Enable
In your config:
```json
{
"config": {
"sample_rate": sample_rate,
"transaction_id": str(uuid.uuid4()),
"model": "hi-banking-v2-8khz",
"parse_number":True
}
}
```
***
#### 🧾 Example
| Mode | Output |
| ----------------------------- | ------------------------------------------------ |
| **Without `parse_number`** | `"घर बनाने के लिए मुझे पच्चीस लाख का लोन चाहिए"` |
| **With `parse_number: True`** | `"घर बनाने के लिए मुझे 2500000 का लोन चाहिए"` |
***
#### 🌐 Language Support
This feature is currently available for:
* Hindi (`hi`)
* Malayalam (`ml`)
* Kannada (`kn`)
* Gujarati (`gu`)
* Marathi (`mr`)
> Want support for another language? Reach out to
***
### 📦 Aux Metadata
Set `aux: true` in your config to receive **server-side diagnostic metadata** along with your transcript response.
This is useful for logging, benchmarking, or correlating timestamps across systems.
#### ✅ How to Enable
```json
{
"aux": true
}
```
***
#### 📘 What You Get
When enabled, each final transcript message will include an `aux_info` block:
```json
"aux_info": {
"request_time": 0.172,
"received_request_time": "2025-05-19T09:32:11.459Z"
}
```
| Field | Description |
| ----------------------- | ------------------------------------------------------------------------------------------------------ |
| `request_time` | Total time in seconds that the server spent handling this request (excluding network transfer delays). |
| `received_request_time` | The timestamp (UTC) when the server received the initial WebSocket connection or request. |
This can help you:
* Profile server-side performance
* Track session start times
* Debug slow or idle sessions
***
---
# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://navana.gitbook.io/bodhi/quickstart/streaming-websocket/advanced-features.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.