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8 changes: 8 additions & 0 deletions chapters/audio-intelligence/index.mdx
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Expand Up @@ -40,6 +40,14 @@ Use these capabilities alongside Live or Pre-recorded STT to automate workflows
Automatically redact names, emails, vehicle IDs, and other PII in pre-recorded transcripts.
</Card>

<Card
title="Sentences"
icon="list-check"
href="/chapters/audio-intelligence/sentences"
>
Group words into sentences with timing for more readable pre-recorded transcripts.
</Card>

<Card
title="Chapterization"
icon="bookmark"
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@@ -1,16 +1,21 @@
---
title: "Sentences"
description: "Semantic sentence segmentation for more readable results"
description: "Semantic sentence segmentation for more readable pre-recorded transcripts"
---

In addition to getting the transcription split by utterances, you can request semantic sentence segmentation for more readable results.
import PrerecordedBadge from "/snippets/badges/prerecorded.mdx"

<PrerecordedBadge />

In addition to getting the transcription split by utterances, you can request semantic sentence segmentation for more readable results. This feature is only available for **pre-recorded** transcription.

<Tip>
You can get translated sentences by enabling both `sentences` and `translation`! You'll receive sentences output for the original transcript, and each `translation` result will also contain sentences in the translated language.
You can get translated sentences by enabling both `sentences` and [translation](/chapters/audio-intelligence/translation)! You'll receive sentences output for the original transcript, and each `translation` result will also contain sentences in the translated language.
</Tip>

```json request data
```json Pre-recorded
{
"audio_url": "YOUR_AUDIO_URL",
"sentences": true
}
```
Expand All @@ -36,4 +41,3 @@ The result will contain a `sentences` key (in addition to `utterances`):
}
```


5 changes: 2 additions & 3 deletions chapters/audio-intelligence/translation.mdx
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Expand Up @@ -9,7 +9,7 @@
<PrerecordedBadge />
<LiveBadge />

The **Translation** model generates translations of your transcriptions to one or more targeted languages. If [subtitles](/chapters/audio-intelligence/subtitles) and/or [sentences](/chapters/pre-recorded-stt/features/sentences) are enabled, the translations will also include translated results for them.
Comment thread
egenthon-cmd marked this conversation as resolved.
The **Translation** model generates translations of your transcriptions to one or more targeted languages. If [subtitles](/chapters/audio-intelligence/subtitles) and/or [sentences](/chapters/audio-intelligence/sentences) are enabled, the translations will also include translated results for them.
You can translate your transcription to **multiple languages** in a single API call.

The list of the languages covered by the Translation feature are listed in [Supported Languages](/chapters/language/supported-languages).
Expand Down Expand Up @@ -131,13 +131,13 @@
{
words: [
{
word: "Diviser",

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start: 0.20043,
end: 0.7008000000000001,
confidence: 1
},
{
word: "l'infini",

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start: 0.9009500000000001,
end: 1.5614400000000002,
confidence: 1
Expand All @@ -145,20 +145,20 @@
...
],
languages: ["fr"],
full_transcript: "Diviser l'infini dans un temps où moins est plus...",

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utterances: [Array], // Also translated
error: null
},
{
words: [
{
word: "Dividir",

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start: 0.20043,
end: 0.7008000000000001,
confidence: 1
},
{
word: "la infinidad",

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start: 0.9009500000000001,
end: 1.5614400000000002,
confidence: 1
Expand All @@ -166,12 +166,12 @@
...
],
languages: ["es"],
full_transcript: "Dividir la infinidad en un tiempo en que menos es más...",

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utterances: [Array], // Also translated
error: null
}
],
exec_time: 0.6475496292114258,

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error: null
}
}
Expand All @@ -190,9 +190,9 @@
"start": 4.2,
"end": 6.1
},
"original_language": "es",

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"target_language": "en",

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"translated_utterance": {

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"text": "good morning",
"language": "en",
"start": 4.2,
Expand All @@ -204,8 +204,7 @@
</CodeGroup>

<Tip>
If you enabled the `subtitles` generation, those will also benefits from the
translation model.
If you enabled [subtitles](/chapters/audio-intelligence/subtitles) or [sentences](/chapters/audio-intelligence/sentences), those will also benefit from the translation model.
</Tip>

## Best practices
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Expand Up @@ -33,11 +33,11 @@
Below are examples of performance aspects that would be more weighted for domain applications of speech to text:

- <u>Accuracy on noisy backgrounds</u>: for contact centers, telephony, and field recordings.
- <u>Speaker diarization quality</u>: for meeting assistants and multi-speaker calls.

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- <u>Named entity accuracy</u>: for workflows that extract people, organizations, phone numbers, or addresses.
- <u>Domain-specific vocabulary handling</u>: for medical, legal, or financial transcription.
- <u>Timestamp accuracy</u>: for media workflows that need readable, well-timed captions.
- <u>Filler-word handling</u>: for agentic workflows .

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Those choices shape every downstream decision: which dataset to use, which normalization rules to apply, and which metrics to report.

Expand All @@ -54,9 +54,9 @@
| `Meet at Point 14` | `meet at point fourteen` | The normalization should preserve the numbered entity instead of collapsing it into an unrelated form. |
| `Mr. Smith joined at 3:00 PM` | `mister smith joined at 3 pm` | Honorific and timestamp formatting differ, but the transcript content is equivalent. |

One common limitation is "Whisper-style normalization" (OpenAI, 2022): implemented in packages like [`whisper-normalizer`](https://pypi.org/project/whisper-normalizer/). It does not affect numbers, and applies aggressive lowercasing and punctuation stripping.

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Gladia's recommended approach is [`gladia-normalization`](https://github.com/gladiaio/normalization), our open-source library designed for transcript evaluation:

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- `It's $50` -> `it is 50 dollars`
- `Meet at Point 14` -> `meet at point 14`
Expand Down Expand Up @@ -149,7 +149,7 @@
public datasets that match your use case.
</Tip>

For a broader methodology view, see [this benchmark guide](/chapters/pre-recorded-stt/benchmarking), especially the evaluation-goal section above when mapping use cases to dataset types.
For a broader methodology view, see [this benchmark guide](/chapters/how-to-use-gladia/benchmarking), especially the evaluation-goal section above when mapping use cases to dataset types.

## 4. Interpret results carefully

Expand All @@ -173,4 +173,4 @@
- Drawing conclusions from too few samples
- Reporting one average score without any slice analysis
- Not inspecting the reference transcript: if it contains text not present in the audio, for example an intro like "this audio is a recording of...", it will inflate WER across all providers
- Not experimenting with provider configurations: for example, using Gladia's [custom vocabulary](/chapters/audio-intelligence/custom-vocabulary) to improve proper noun accuracy, then comparing against the ground truth

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2 changes: 1 addition & 1 deletion chapters/introduction/index.mdx
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@@ -1,5 +1,5 @@
---
title: Welcome to Gladia

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description: "The most reliable state-of-the-art Speech-To-Text API provider"
mode: "wide"
---
Expand All @@ -18,7 +18,7 @@
/>


Gladia is a state-of-the-art audio transcription and intelligence provider. We offer a simple API to get transcription from your audios and videos,

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in both Real-time and asynchronous ways, with audio intelligence tools to extract, analyze and understand data from your audios.


Expand All @@ -37,13 +37,13 @@
icon="magnifying-glass-chart"
href="/chapters/audio-intelligence/"
>
Use the power of LLMs directly on your audios without a third party service.

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</Card>

<Card
title="Test gladia playground"
icon="list-music"
href="/chapters/introduction/playground"
href="/chapters/how-to-use-gladia/playground"
arrow={false}
>
Test gladia quickly on our playground.
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---
title: Models
description: Compare Gladia speech-to-text models and choose the right one for your use case.

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---

Pick a model with `model` in your request. Omit it to use the default: **`solaria-1`**.

## Choose your model

<CardGroup cols={2}>
<Card title="Solaria-3" icon="sparkles" href="#solaria-3">
Highest accuracy on European real-world audio. Pre-recorded only.
</Card>
<Card title="Solaria-1" icon="globe" href="#solaria-1">
Default generalist. 100+ languages, async and live, code switching.
</Card>
</CardGroup>

## Comparison

| | **Solaria-3** | **Solaria-1** (default) |
| --- | --- | --- |
| **Best for** | European real-world / business audio | Global coverage across any domain |
| **Modes** | Pre-recorded only | Pre-recorded + live |
| **Languages** | EN, FR, DE, ES, IT | 100+ languages |
| **Code switching** | No | Yes |
| **Benchmarks** | Optimized for real-world European production audio. [See WER results →](https://www.gladia.io/competitors/benchmarks) | Optimized for clean speech, live streaming, and multilingual coverage. [See WER results →](https://www.gladia.io/competitors/benchmarks) |
| **Audio Intelligence** | All add-ons | All add-ons |
| **Pricing** | [Same plan rates](https://www.gladia.io/pricing) | [Same plan rates](https://www.gladia.io/pricing) |

## Select a model in your API call

Set `model` to `"solaria-3"` or `"solaria-1"`:

<CodeGroup>

```javascript JavaScript
import { GladiaClient } from "@gladiaio/sdk";

const gladiaClient = new GladiaClient({ apiKey: "YOUR_GLADIA_API_KEY" });

const transcription = await gladiaClient.preRecorded().transcribe(
"YOUR_AUDIO_URL_OR_LOCAL_PATH",
{
model: "solaria-3",
language_config: {
languages: ["fr"],
},
}
);
```

```python Python
from gladiaio_sdk import GladiaClient

gladia_client = GladiaClient(api_key="YOUR_GLADIA_API_KEY").prerecorded()

transcription = gladia_client.transcribe(
"YOUR_AUDIO_URL_OR_LOCAL_PATH",
{
"model": "solaria-3",
"language_config": {
"languages": ["fr"],
},
},
)
```

```bash cURL
curl --request POST 'https://api.gladia.io/v2/pre-recorded' \
--header 'x-gladia-key: YOUR_GLADIA_API_KEY' \
--header 'Content-Type: application/json' \
--data-raw '{
"audio_url": "YOUR_AUDIO_URL",
"model": "solaria-3",
"language_config": {
"languages": ["fr"]
}
}'
```

</CodeGroup>

<Note>
With `"solaria-3"`, there is no code switching. You can pass languages in `language_config.languages` (for example `["fr"]`, or several from EN/FR/DE/ES/IT) so the model can pick among those covered languages. Once the language is detected, it sticks to it for the rest of the file.
</Note>

## Solaria-3

Highest accuracy on noisy, conversational European audio (calls, meetings, field recordings).

### When to use

Use **`solaria-3`** if:

- Audio is **pre-recorded**
- Language is **EN, FR, DE, ES, or IT**
- You prioritize **accuracy on real production audio**
- You can constrain detection to the **covered languages** (no mid-file switching)

Use Solaria-1 instead for live streaming, code switching, languages outside those five, or clean / formal speech.

### Get started

<CardGroup cols={2}>
<Card
title="Pre-recorded transcription"
icon="file-audio"
href="/chapters/pre-recorded-stt/quickstart"
>
Transcribe files with `model: "solaria-3"`.
</Card>
<Card
title="SDK integration"
icon="code"
href="/chapters/integrations/sdk"
>
Call Solaria-3 from JavaScript or Python.
</Card>
</CardGroup>

## Solaria-1

Maximum language coverage. Works async and live, with code switching.

### When to use

Use **`solaria-1`** (or omit `model`) if:

- You need **live / real-time** transcription
- You need **100+ languages** or **code switching**
- Audio is **clean read-speech** or formal / institutional

Ideal default for voice agents, live captions, and global multilingual products.

### Get started

<CardGroup cols={3}>
<Card
title="Live transcription"
icon="bolt"
href="/chapters/live-stt/quickstart"
>
Stream audio in real time.
</Card>
<Card
title="Pre-recorded transcription"
icon="file-audio"
href="/chapters/pre-recorded-stt/quickstart"
>
Batch-transcribe with the default model.
</Card>
<Card
title="SDK integration"
icon="code"
href="/chapters/integrations/sdk"
>
Integrate with the official SDKs.

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</Card>
</CardGroup>

<CardGroup cols={2}>
<Card
title="Code switching"
icon="language"
href="/chapters/language/code-switching"
>
Handle mixed-language conversations.
</Card>
<Card
title="Supported languages"
icon="globe"
href="/chapters/language/supported-languages"
>
Full language list.
</Card>
</CardGroup>

<Tip>
Compare Solaria-3 and Solaria-1 WER across real customer audio and public datasets on our [open benchmarks page](https://www.gladia.io/competitors/benchmarks). To measure accuracy on your own traffic, see [Benchmarking](/chapters/how-to-use-gladia/benchmarking).
</Tip>
7 changes: 7 additions & 0 deletions chapters/pre-recorded-stt/audio-intelligence.mdx
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Expand Up @@ -34,6 +34,13 @@ Audio intelligence turns raw speech into structured, useful data on top of trans
>
Generate ready-to-use subtitle files in SRT or VTT formats.
</Card>
<Card
title="Sentences"
icon="list-check"
href="/chapters/audio-intelligence/sentences"
>
Group words into sentences with timing for more readable pre-recorded transcripts.
</Card>
<Card
title="Custom vocabulary"
icon="spell-check"
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---
title: Pre-recorded Features
description: "Core features of the Gladia Pre-recorded STT API"

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---

The core functionality of the Gladia API is its Speech Recognition model, designed to convert spoken language into written text. Additional capabilities like diarization, summarization, translation, custom prompts and more can be enabled by adding parameters to your request.

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<CardGroup cols={3}>
<Card
title="Speaker Diarization"

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icon="user-group"
href="/chapters/pre-recorded-stt/features/speaker-diarization"
>
Expand Down Expand Up @@ -51,7 +51,7 @@
<Card
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title="Sentences"
icon="list-check"
href="/chapters/pre-recorded-stt/features/sentences"
href="/chapters/audio-intelligence/sentences"
>
Group words into sentences with timing for better readability and parsing.
</Card>
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| `diarization_config.min_speakers` / `max_speakers` | Set a range (e.g. `2`-`10`) | Meeting size varies — a range lets the model adapt without over- or under-splitting speakers. |
| `summarization` | `true` | Generates a summary for quick review. Use `bullet_points` type for action-item style output. See [Summarization](/chapters/audio-intelligence/summarization). |
| `named_entity_recognition` | `true` | Surfaces people, organizations, dates, and other key entities mentioned during the meeting. See [NER](/chapters/audio-intelligence/named-entity-recognition). |
| `sentences` | `true` | Produces well-segmented, readable output suitable for meeting minutes. See [Sentences](/chapters/pre-recorded-stt/features/sentences). |
| `sentences` | `true` | Produces well-segmented, readable output suitable for meeting minutes. See [Sentences](/chapters/audio-intelligence/sentences). |
| `language_config.languages` | Set explicitly | Meeting language is almost always known in advance — setting it avoids detection overhead. |
| `custom_vocabulary` | `true` | Add company-specific terms, project names, and participant names for better accuracy. |

Expand All @@ -58,7 +58,7 @@

## Call Centers

For recorded phone calls the priorities are **speaker identification** and **accurate transcription** despite variable audio quality (telephony codecs, background noise, cross-talk).

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| Parameter | Recommended value | Why |
| --------------------------------------- | ------------------------------ | --------------------------------------------------------------------------------------------------------------------------- |
Expand All @@ -80,7 +80,7 @@
| -------------------------------------------------- | -------------------------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `diarization` | `true` | Essential for multi-speaker content. |
| `diarization_config.min_speakers` / `max_speakers` | Set a range (e.g. `2`-`4`) | Provides a flexible hint when the exact count varies across episodes. |
| `sentences` | `true` | Produces well-segmented, readable output suitable for publishing. See [Sentences](/chapters/pre-recorded-stt/features/sentences). |
| `sentences` | `true` | Produces well-segmented, readable output suitable for publishing. See [Sentences](/chapters/audio-intelligence/sentences). |
| `custom_vocabulary` | `true` | Add recurring guest names, show-specific terms, and brand names. |
| `language_config.languages` | Set explicitly | Podcast language is almost always known in advance. |

Expand All @@ -88,7 +88,7 @@

## Subtitles & Captioning

When generating subtitle files from pre-recorded content, tune the formatting parameters for the best viewing experience. Gladia produces SRT and VTT files directly — no post-processing needed. See [Subtitles](/chapters/audio-intelligence/subtitles) for the full parameter reference.

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| Parameter | Recommended value | Why |
| --------------------------------------------- | ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------ |
Expand All @@ -100,7 +100,7 @@
| `translation` | `true` (if needed) | When enabled, subtitles are automatically generated for each target language. See [Translation](/chapters/audio-intelligence/translation). |

<Tip>
For live captions streamed in real time, use the [Realtime

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chapters/pre-recorded-stt/recommended-parameters.mdx#L103

Did you really mean 'Realtime'?
API](/chapters/live-stt/quickstart) with partial transcripts instead — see the
[Live recommended
parameters](/chapters/live-stt/recommended-parameters#subtitles--captioning)
Expand All @@ -122,5 +122,5 @@
<Warning>
Do not enable `code_switching` with an empty `languages` list. The detector
would evaluate every utterance against 100+ languages, leading to frequent
misdetections — especially between similar-sounding languages.

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Did you really mean 'misdetections'?
</Warning>
24 changes: 21 additions & 3 deletions docs.json
Original file line number Diff line number Diff line change
Expand Up @@ -29,8 +29,14 @@
"pages": [
"chapters/introduction/index",
"chapters/introduction/getting-started",
"chapters/introduction/playground",
"chapters/pre-recorded-stt/benchmarking"
"chapters/introduction/models"
]
},
{
"group": "How to use Gladia",
"pages": [
"chapters/how-to-use-gladia/playground",
"chapters/how-to-use-gladia/benchmarking"
]
},
{
Expand All @@ -42,7 +48,6 @@
"pages": [
"chapters/pre-recorded-stt/quickstart",
"chapters/pre-recorded-stt/audio-intelligence",
"chapters/pre-recorded-stt/features/sentences",
"chapters/pre-recorded-stt/recommended-parameters"
]
},
Expand Down Expand Up @@ -74,6 +79,7 @@
"chapters/audio-intelligence/speaker-diarization",
"chapters/audio-intelligence/translation",
"chapters/audio-intelligence/subtitles",
"chapters/audio-intelligence/sentences",
"chapters/audio-intelligence/custom-vocabulary",
"chapters/audio-intelligence/custom-spelling",
"chapters/audio-intelligence/named-entity-recognition",
Expand Down Expand Up @@ -306,6 +312,18 @@
}
},
"redirects": [
{
"source": "/chapters/introduction/playground",
"destination": "/chapters/how-to-use-gladia/playground"
},
{
"source": "/chapters/pre-recorded-stt/benchmarking",
"destination": "/chapters/how-to-use-gladia/benchmarking"
},
{
"source": "/chapters/pre-recorded-stt/features/sentences",
"destination": "/chapters/audio-intelligence/sentences"
},
{
"source": "/api-reference/transcription-flow",
"destination": "/api-reference/pre-recorded-flow"
Expand Down