During its inaugural Developer Day, AI startup OpenAI released a series of open-source models. The slew of products included an upgraded version of its open-source automatic speech recognition model, Whisper large-v3. The company’s future plans involve making the model’s API accessible to users.
The models for English-only applications tend to perform better, especially for the `tiny.en` and `base.en` models as per the official page. The model’s performance varies widely depending on the language.
(Source: OpenAI)
Initially focused on English, the neural net model was released in September last year. Then it got an upgraded version 2 in December which was enhanced to support multiple languages, although specific languages were not explicitly mentioned.
Accessible on GitHub under a permissive license, Whisper large-v3 effortlessly transcribes various content for users and has been called the best transcription tool out there. The model features a unique timestamp section that facilitates its application as subtitles on platforms such as YouTube.
The tool initiates the process by segmenting audio into 30-second clips, converting them, and subsequently passing them through an encoder and decoder, which predict the corresponding text caption. Technical intricacies also involve language identification, facilitating multilingual speech transcription, and translation to English.
The model was initially expected to be integrated with ChatGPT, to let the users converse directly with the chatbot through speech. But OpenAI then decided to release the model to the public directly. Interestingly, Whisper is not aimed at the end users as of now but rather at researchers.
The reason for open-sourcing as per OpenAI was to “serve as a foundation for building useful applications and for further research on robust speech processing“. OpenAI’s AI tool was honed using an extensive dataset of 680,000 hours of meticulously supervised data sourced from the internet, with one third portion originating from non-English sources.
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