![]() To learn more about the paper, model card, and additional details on Whisper, click here. OpenAI hopes that the model’s ease of use and high accuracy will allow developers to add voice interfaces to a wider set of applications. When measured, findings show that Whisper’s zero-shot performance across many diverse datasets is robust-making 50% fewer errors than other models. Since Whisper was trained on a large, diverse dataset (about a third of which is non-English audio dataset) without being fine-tuned to any specific one, it does not beat models that specialise in LibriSpeech performance. The company says that other existing approaches frequently use smaller, more closely paired audio-text training datasets or broad but unsupervised audio pretraining. A decoder is trained to predict the corresponding text caption, intermixed with special tokens that direct the single model to perform tasks such as language identification, phrase-level timestamps, multilingual speech transcription, and to-English speech translation.” Being open source means that if you have the hardware, it can be run within your own network providing. It is a fully open source STT engine, based on Baidu’s Deep Speech architecture and implemented with Google’s TensorFlow framework. ![]() Input audio is split into 30-second chunks, converted into a log-Mel spectrogram, and then passed into an encoder. Mycroft has been supporting Mozillas efforts to build DeepSpeech, an open Speech-to-Text technology. The company’s open-sourced models and inference code serve as a foundation for building useful applications and boost further research on robust speech processing.Īn excerpt from the blog reads, “The Whisper architecture is a simple end-to-end approach, implemented as an encoder-decoder Transformer. It claims to have an improved recognition of background noise, unique accents, and technical jargon owing to the use of such a large and diverse dataset. The model is trained on 680,000 hours of multilingual and multitask supervised data collected from the web. But OpenAI claims that Whisper stands out. Numerous organisations such as Google, Meta and Amazon have developed highly capable speech recognition systems. ![]() In a blog post last week, OpenAI introduced Whisper-a multilingual, automatic speech recognition system that is trained and open sourced to approach human level robustness and accuracy on English speech recognition. However, OpenAI has just moved one step closer to solving it. Speech recognition remains a challenge in AI.
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