Models and Languages#
We build only high accuracy speech recognition AI solutions that enable you to transcribe any audio and get back highly accurate transcripts. For comparison with other providers, please see our benchmarks.
We support two types of models: default and low-latency. The default model provides the highest accuracy (much higher than low-latency) and should be used for almost all use cases (e.g. transcribing files, meetings, phone calls, voice interactions). The low-latency model should be used only when instant recognition is required (e.g. live captioning).
|Language||Model name||Model type||Speaker AI Supported|
You must configure the model by setting the
TranscriptionConfig field to
a valid model name (e.g.,
en_v2). Refer to Configure Requests.
Do not forget to specify the model, as specifing no model will result in a legacy English model being used.
For all non-English languages, Soniox’s speech recognition AI is a bilingual solution,
meaning that it can recognize both the native and English language.
For example, the model
ko_v2 can recognize both Korean and English with high accuracy.
Note that English models (
en_v2_lowlatency) have higher accuracy on
English only audio, therefore it is recommended to use the English models when the entire audio
or large audio segment is in English language.
Default vs Low-Latency Model#
You should consider using the low-latency model only when instant recognition of words is required.
Typical use cases include live captioning and live dictation.
The low-latency processing mode is enabled by setting the
model to a low-latency model (e.g.
en_v2_lowlatency) and by setting the
enable_nonfinal field to
The low-latency model can be only used with streaming API calls.
However, our streaming API calls also support the default model, allowing you to transcribe the stream with maximum accuracy. However, this may result in many seconds of latency for the recognized words. This is particularly useful for applications where you can send the audio in real-time and obtain the entire transcript as soon as possible after the end of the audio. Typical use cases for this would include voice interactions.
Spaces in Chinese Models#
With Chinese models, predicted space tokens should be treated somewhat differently. A space token represents either a physical space or a suggestion where a line break may occur. While the distinction is not provided by the model, a simple heuristic can be used: treat the space as a possible line break when it is, on both sides, adjacent to a Chinese character or a Chinese (full-width) punctuation symbol.