The right parameter configuration can significantly impact transcription quality for pre-recorded audio. This guide covers recommended starting points for common scenarios and highlights pitfalls that frequently trip up new integrations.
These recommendations apply to the Pre-recorded
API and are passed in the POST /v2/pre-recorded request body. They are starting points — tune them to match
your specific needs.
Language Configuration
One of the most common configuration mistakes is misunderstanding how language_config works. Choosing the right setup avoids unnecessary detection overhead and improves accuracy.
When to set an explicit language:
- You know the language of the audio ahead of time.
- The audio is monolingual (single language throughout).
- You want the fastest, most accurate results.
{
"language_config": {
"languages": ["en"],
"code_switching": false
}
}
- You process audio in many different languages and don’t know which one beforehand.
- You want Gladia to pick the language automatically.
{
"language_config": {
"languages": [],
"code_switching": false
}
}
When code_switching is false and no language is set, the language is
detected on the first utterance and reused for the rest of the session or
file. If the beginning of your audio contains silence, music, or a different
language than the main content, this can lead to incorrect detection for the
whole transcription.
Even when using auto-detection, pass a small list of likely languages in
languages to constrain the search. This improves both accuracy and
processing time.
Code Switching
Code switching (language_config.code_switching: true) lets Gladia detect and transcribe multiple languages within the same audio, re-evaluating the language on each utterance.
When to enable it:
- Speakers switch languages mid-conversation (e.g. bilingual meetings, multilingual customer support).
- You need the detected
language returned per utterance.
When NOT to enable it:
- The audio is in a single language — code switching adds unnecessary processing and can introduce misdetections.
- You’ve set exactly one language in
languages — in that case code_switching is ignored anyway.
{
"language_config": {
"languages": ["en", "fr", "es"],
"code_switching": true
}
}
Do not enable code_switching with an empty languages list. When no
languages are specified, the language detector evaluates every utterance
against 100+ supported languages, which leads to frequent misdetections —
especially between similar-sounding languages. Always provide a short list of
languages you actually expect in the audio.
Custom Vocabulary
Custom vocabulary is a post-transcription replacement based on phoneme similarity. It’s essential for domain-specific terms that speech models frequently mis-transcribe.
Best practices:
- Always provide both the
custom_vocabulary flag and a custom_vocabulary_config.
- Add pronunciations for words that can be said in different ways (accents, foreign speakers). This is more reliable than raising
intensity.
- Keep
intensity moderate (0.4-0.6). High values increase false positives where unrelated words get replaced.
- Set
language on individual vocabulary entries when your audio is multilingual and a term is pronounced differently depending on the language.
For simple terms that are already close to their phonetic spelling (e.g. brand
names), you can pass them as plain strings instead of objects — Gladia will
use the default intensity.
{
"audio_url": "YOUR_AUDIO_URL",
"custom_vocabulary": true,
"custom_vocabulary_config": {
"vocabulary": [
"Kubernetes",
{
"value": "Gladia",
"pronunciations": ["Gladya", "Gladiah"],
"intensity": 0.5
},
{
"value": "PostgreSQL",
"pronunciations": ["Postgres Q L", "Post gress"],
"intensity": 0.4
}
],
"default_intensity": 0.5
}
}
Meeting Recorders
For apps that record and process meetings — team stand-ups, board sessions, 1-on-1s — the goal is to produce structured, actionable meeting notes with clear speaker attribution. Meetings typically have a known set of participants and benefit heavily from post-processing features like summarization.
| Parameter | Recommended value | Why |
|---|
diarization | true | Attributes speech to each participant. See Speaker diarization. |
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. |
named_entity_recognition | true | Surfaces people, organizations, dates, and other key entities mentioned during the meeting. See NER. |
sentences | true | Produces well-segmented, readable output suitable for meeting minutes. See 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. |
Diarization vs. multi-channel: if each speaker is on a separate audio channel (e.g. a, use the channel field on each utterance to identify who is speaking — diarization is not needed. See Multiple channelsIf all speakers share a single audio channel, enable diarization to separate the speakers. See Speaker diarization.
Call Centers
For recorded phone calls the priorities are speaker identification and accurate transcription despite variable audio quality (telephony codecs, background noise, cross-talk).
| Parameter | Recommended value | Why |
|---|
language_config.languages | Set explicitly (e.g. ["en"]) | Call center audio typically has a known language. Setting it avoids detection errors on noisy recordings. |
diarization | true | Separates agent and customer speech. See Speaker diarization. |
diarization_config.number_of_speakers | 2 | Most calls have exactly two participants — giving this hint improves speaker assignment accuracy. |
custom_vocabulary | true | Add product names, plan names, and internal terminology. |
summarization | true | Automatically generates a summary for agent wrap-up notes. See Summarization. |
Diarization vs. multi-channel: if each speaker is on a separate audio channel (e.g. a, use the channel field on each utterance to identify who is speaking — diarization is not needed. See Multiple channelsIf all speakers share a single audio channel, enable diarization to separate the speakers. See Speaker diarization.
Podcasts & Interviews
For long-form audio with multiple speakers the focus is on readability and correct speaker attribution. Transcripts are often repurposed as articles or show notes, so segment quality matters.
| Parameter | Recommended value | Why |
|---|
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. |
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. |
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 for the full parameter reference.
| Parameter | Recommended value | Why |
|---|
subtitles | true | Enables subtitle generation. |
subtitles_config.formats | ["srt", "vtt"] | Generate both formats to cover different players and platforms. |
subtitles_config.maximum_characters_per_row | 42 | Standard broadcast limit for readability. |
subtitles_config.maximum_rows_per_caption | 2 | Keeps captions compact on screen. |
subtitles_config.style | "compliance" | Uses stricter formatting rules suited for broadcast or accessibility requirements. |
translation | true (if needed) | When enabled, subtitles are automatically generated for each target language. See Translation. |
Multilingual Content
For content with mixed languages — conferences, multilingual media, interviews with speakers from different countries — combine language detection with code switching.
| Parameter | Recommended value | Why |
|---|
language_config.languages | List of expected languages (e.g. ["en", "fr", "de"]) | Constrain to 3-5 expected languages for best accuracy. |
language_config.code_switching | true | Detects language shifts across utterances. See Code switching. |
custom_vocabulary | true | Add terms for each language with appropriate language tags on each entry. |
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.
