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Ai voice transcription12/2/2023 There’s a distinction to be made between general-use-case transcription and transcription for AI. In this article, we’ll discuss why human transcription is still necessary in an increasingly automated world and why we take a consultancy approach to transcription for AI. ![]() Therefore, when you consider the unique (and sometimes strange) training data needs of today’s speech technology developers, a one-size-fits-all approach to speech transcription is destined for failure.īefore starting a transcription project, you have to consider your project factors such as use case, budget, quality requirements, necessary language expertise, and more. When clients come to us for speech data collection and transcription, they’re trying to solve for the edge cases where ASR still struggles-whether it’s recognizing a greater variety of accents or dealing with background noise. That’s because automatic speech recognition (ASR) already covers the simple transcription cases. But as a data provider to AI developers, the transcription projects on our plates today are anything but simple. Speech transcription is a simple task on the surface: write down what was said in an audio recording. But when your goal is to further improve the accuracy of automatic speech recognition, you’ll still need the help of real-life human transcribers. AISense plans to implement a subscription model to access extra features later on.Automatic speech transcription has reached near-human accuracy levels at a fraction of the cost and effort. After all, who transcribes speech for the fun of it?īetter try it out while it's still free, though. Still, for those who do interviews, take copious notes during classes or meetings, or would simply like a hands-free way to record their thoughts as text, an app like Otter could make life much easier. Plus, you can't transfer audio recordings not done directly using the app. Otter has certain issues with punctuation, which it tends to leave out, and has difficulty working in crowded places or with loud noise in the background. Otter's AI also automatically puts tags in every recording and transcription you save for easier file management. Also, the raw transcript of a live conversation you're recording appears almost immediately in front of you. ![]() Why does it need to identify you? Well, because Otter's live transcriptions are ideally separated by each speaker. Otter saves your voice and tags your transcriptions. These become the basis for your "voiceprint" so that Otter can identify you in the recordings you make. As soon as you install the app, available for free for both Android and Apple users, it asks you to do a short and long recording - which you start by pressing the app's mic icon. Otter has a rather simple but intuitive approach to voice transcriptions. A few years ago, this system wouldn't be usable," he told Cnet. "With AI tech and deep learning in the last few years, the accuracy for speech recognition has improved dramatically. VoiceprintsĪll of these developments made it possible to design the Otter app, Liang explained. Google's DeepMind proved it can already mimic human speech with astonishing accuracy and clarity. On top of this, promising algorithms have been built to produce synthetic speech. In fact, Amazon is supposedly close to developing another "real-time speech translation" service using Alexa. There are speech recognition algorithms, which most of us are familiar with because of virtual assistants trained to "talk" to us - Apple's Siri, Amazon's Alexa, and Google's creatively named Assistant. This app not only has market trends working in its favor, but it also benefited from a ton of work that has been done recently on voice and AI. "This is a perfect time," AISense CEO and founder Sam Liang told CNet. ![]() There was a market ready for Otter to penetrate, as it proved during its launch at the Mobile World Congress this past week. ![]() AISense, the startup that developed Otter, saw an opportunity here.
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