Models
Speechmatics offers three models for Speech to Text: Enhanced, Standard, and Melia 1. All three use the same API. The model you choose determines accuracy, how multilingual audio is handled, and which processing modes and regions are available.
Compare the models
Enhanced and Standard are feature-identical and differ only in accuracy and speed: Enhanced delivers the highest accuracy, and Standard prioritizes throughput. Melia 1 matches Standard for accuracy and adds automatic multilingual transcription, but it is available for Batch only and supports a reduced feature set. Speech intelligence covers translation, summarization, topic detection, chapters, sentiment, and audio events.
Melia 1 matches the Enhanced and Standard models for core transcription features, including diarization, word timings, punctuation, notifications, and output locale. It does not yet support the following features, which are available with the Enhanced and Standard models:
- Custom vocabulary and formatting: custom dictionary, find and replace, spoken form output, profanity tagging
- Output detail: confidence scores, entity detection, audio filtering
- Speaker identification
- Speech intelligence: audio events, translation, summarization, chapters, topics, sentiment
Melia 1 is an early-access model and its feature support is expanding. Check the release notes for the latest.
Choose a model
Use Enhanced for the highest accuracy on single-language audio, such as medical, legal, or subtitling work.
Use Standard when throughput or latency matter more than maximum accuracy, such as archival transcription, content indexing, or large-scale captioning.
Use Melia 1 for audio that contains more than one language, including speakers who switch language mid-conversation.
For healthcare use cases, use the Enhanced Medical model which is tuned for medical terminology.
Specify a model
Set the model property in your transcription config. If you do not set it, the standard model is used.
This config selects the enhanced model:
{
"type": "transcription",
"transcription_config": {
"model": "enhanced",
"language": "en"
}
}
Enhanced and Standard are available for Realtime and Batch transcription. Melia 1 is available for Batch transcription only.
Melia 1
Melia 1 is a multilingual model. It transcribes audio that contains more than one language, including speakers who switch language mid-conversation, and returns a single continuous transcript. It does not require you to select a language pack, and its accuracy is on par with the Standard model.
Set "model": "melia-1" and "language": "multi":
{
"type": "transcription",
"transcription_config": {
"model": "melia-1",
"language": "multi"
}
}
Melia 1 does not support the auto language value, which returns an error. Set language to multi.
Melia 1 is available for Batch transcription in the EU and US regions only. It is not available in the Australia (AU1) region.
For the full list of Batch endpoints, refer to Authentication.
For the features Melia 1 does not yet support, refer to Compare the models.
To configure language hints and read the per-language output metadata, refer to Input and Output.
Enhanced Medical model
Speechmatics offers the Enhanced Medical model that delivers high accuracy on healthcare audio such as ambient scribes and dictation tools.
The Enhanced Medical model is kept up to date using officially maintained data sources. This improves recognition of medical terminology such as procedures, medications, conditions, and anatomy.
For languages not listed below, the Enhanced model still delivers high accuracy on healthcare audio without the medical domain.
To use the Enhanced Medical model, set the domain property to medical:
{
"type": "transcription",
"transcription_config": {
"model": "enhanced",
"language": "en",
"domain": "medical"
}
}
Operating points
The model property replaces the operating_point property. Existing configs that use operating_point continue to transcribe without changes.
In SaaS (cloud) deployments, operating_point is deprecated. It maps to model and accepts the same enhanced and standard values. Use model going forward.