Check out the AssemblyAI changelog to see weekly accuracy and product improvements our team has been working on.
Powering incredible companies
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We’ve fixed two edge cases in our async transcription pipeline that were producing non-deterministic results from multilingual and stereo audio.
We’ve improved word boundary detection in our Japanese automatic speech recognition model. These changes are effective immediately for all Japanese audio files submitted to AssemblyAI.
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We’ve implemented a range of improvements to our English pipeline, leading to an average 38% improvement in overall latency for asynchronous English transcriptions.
We’ve made improvements to our password reset process, offering greater clarity to users attempting to reset their passwords while still ensuring security throughout the reset process.
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We're excited to announce that our new Conformer-1 Speech Recognition model is now available for real-time English transcriptions, offering a 24.3% relative accuracy improvement.
Effective immediately, this state-of-the-art model will be the default model for all English audio data sent to the wss://api.assemblyai.com/v2/realtime/ws WebSocket API.
The Speaker Labels model now accepts a new optional parameter called speakers_expected. If you have high confidence in the number of speakers in an audio file, then you can specify it with speakers_expected in order to improve Speaker Labels performance, particularly for short utterances.
TLS 1.3 is now available for use with the AssemblyAI API. Using TLS 1.3 can decrease latency when establishing a connection to the API.
Our PII redaction scaling has been improved to increase stability, particularly when processing longer files.
We've improved the quality and accuracy of our Japanese model.
Short transcripts that are unable to be summarized will now return an empty summary and a successful transcript.
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We've released our new Conformer-1 model for speech recognition. Conformer-1 was trained on 650K hours of audio data and is our most accurate model to date.
Conformer-1 is now the default model for all English audio files sent to the /v2/transcript endpoint for async processing.
We'll be releasing it for real-time English transcriptions within the next two weeks, and will add support for more languages soon.
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Our Content Safety and Topic Detection models are now available for use with Italian audio files.
We’ve made improvements to our Japanese punctuation model, increasing relative accuracy by 11%. These changes are effective immediately for all Japanese audio files submitted to AssemblyAI.