Real time speech processing is getting a major upgrade with Meta’s new Muse Voice Transcribe model. Developed by Meta Superintelligence Labs, it is the company’s first real time audio perception model and supports more than 70 languages, including Hindi, Tamil, Telugu, Kannada and Malayalam.
Real time transcription with speaker separation
Muse Voice Transcribe converts speech into text as it happens. It can also identify individual speakers and detect when a person starts or stops speaking. These functions work together as the audio arrives, without requiring separate post processing.
The model can distinguish more than 20 speakers in a recording and handle audio longer than 1 hour. It processes sound in 80 millisecond chunks and decides when there is enough information to transcribe each word. It can delay harder words while committing simpler ones faster. Meta says reinforcement learning helps the model manage these delays while keeping transcription errors low.
Meta trained the model across more than 70 languages and extensively validated 25 languages for the initial release. Its supported languages include 5 major Indian languages: Hindi, Tamil, Telugu, Kannada and Malayalam.
Supports multilingual conversations
The model can also handle code switching, including language changes within the same sentence. Users do not need to manually change the language whenever speakers switch languages.
Muse Voice Transcribe also supports language, keyword and context biasing. This helps the model recognise words based on the audio and the wider conversation.
Availability and pricing
Meta has made Muse Voice Transcribe available through the Meta Model API, allowing developers to use it for speech transcription in their own applications. Meta AI for Mac and Muse Code already use the model for dictation.
The API costs $3 (roughly Rs. 300) per 1,000 audio minutes, which is about $0.18 (roughly Rs. 17) per hour.
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