Speechbox is a new tool that utilizes the power of machine learning to enhance the accuracy and usefulness of audio transcriptions. It is built on the premise that the Whisper language model is robust enough to transcribe a wide range of English speech accurately. Furthermore, Whisper was specifically trained to predict punctuated and orthographic text, which makes it well-suited for use in Speechbox.
The basic idea behind Speechbox is to “unnormalize” audio transcriptions, which means converting them into a more useful format for downstream applications while ensuring that the exact same words are being used. For example, the sentence “we are going to marina bay sands” can have multiple meanings depending on the context. Without proper punctuation, it is unclear whether the speaker is excited about the plan to go to the beach, asking a question about whether they are going to the beach or not, or making a statement about their current direction. Some capitalization also needs to be done to make it a better transcription of speech.
Using Whisper to add appropriate punctuation and capitalization, Speechbox can disambiguate the meaning of the sentence and make it much more useful for other downstream applications. In the example above, Whisper would add the appropriate punctuation to make it clear that the speaker is making a statement about their plans, and he/she is excited about it: “We are going to the San Francisco beach!”
Speechbox is not only useful for improving the accuracy of audio transcriptions but also for other applications such as automated captioning, speech-to-text, and sentiment analysis. By providing cleaned-up and punctuated text, Speechbox can help these other applications function more effectively and produce more accurate results.
One of the key advantages of Speechbox is that it is based on an advanced language model like Whisper, which can understand and process a wide range of complex language patterns. This means that Speechbox is able to handle a wide variety of input, from clear and well-spoken speech to more mumbled or accented speech.
Overall, Speechbox is a powerful tool for anyone who needs to work with audio transcriptions. Using Whisper to “unnormalize” audio transcriptions makes them more useful for downstream applications while preserving the exact same words. This makes it an ideal solution for a wide range of applications, from automated captioning and speech-to-text to sentiment analysis.
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Vineet Kumar is a consulting intern at MarktechPost. He is currently pursuing his BS from the Indian Institute of Technology(IIT), Kanpur. He is a Machine Learning enthusiast. He is passionate about research and the latest advancements in Deep Learning, Computer Vision, and related fields.