![]() ![]() But there are many other important signals such as what the user has listened to, highlighted, and saved, or what is currently trending among other users.” “Whether the user is subscribed to a certain show is a strong signal, which is why a lot of the shown content comes from a user’s subscriptions. “The goal of the algorithm is to present the user with content they are interested in - for this, we use various signals,” Snipd co-founder Kevin Smith explained to TechCrunch. This means that the episode feed is not based purely on users’ podcast subscriptions, as it also pulls in content that Snipd thinks they will be interested in based on their chosen subjects, among other “signals.” “history” or “music”), which Snipd uses to generate these highlights. It’s worth noting that with the app’s latest update, users are now asked to select their favorite topics (e.g. Image Credits: Snipdįrom there, listeners can save each clip to their library, or - if they like what they’re hearing from the short segment that Snipd has presented - jump directly into the full podcast episode. “TikTok”-inspired feed of podcast highlights. But Snipd is striving to be much more than another podcatcher, in terms of how it analyzes the content of episodes to help listeners curate and get to the heart of the details that matter.įor example, Snipd can create “chapters,” which separates each episode into navigable segments with their own title, while it can also generate transcripts of entire shows. Similar to other so-called “podcatcher” apps, Snipd works by users searching and subscribing to podcasts that are of interest to them - this could be anything from true crime to history and sport. One of these is Snipd, a Swiss startup building a podcast app that uses AI to transcribe content and synchronize with note-taking apps, automatically generate book-style “chapters” and, as of this week, deliver podcast highlights in a TikTok-style personalized feed. Against that backdrop, major players in the field are bolstering their podcasting armory, with Spotify recently doling out around $85 million for two companies specializing in podcast measurement and analytics, while Acast recently snapped up Podchaser - an “IMDb for podcasts” that gives advertisers deeper data insights - in a $27 million deal.īut as the big platforms lock horns in the hunt for podcasting riches, smaller players continue to arrive on the scene with their own ideas on how to advance the podcast medium for creators and consumers alike. alone expected to hit $2 billion this year - a figure that’s set to double by 2024. Then add pauses and adjust the speed and pitch as needed.Podcasting has emerged as a major billion-dollar industry, with ad revenue in the U.S. Some voices were much better than others. The differences were stark in my testing. Murf offers multiple voices - male, female, educator, developer, more. Paste the text into the tool, and it will generate the audio. It’s handy for creating video voiceovers - such as for YouTube and TikTok - and audio versions of articles. Murf is an AI voice generator to turn text into speech. MeetGeek is a close alternative to Otter. “Pro” and “Business” plans cost $8 and $20 per month, billed annually. ![]() Otter’s free “Basic” plan includes 300 monthly transcription minutes - 30 minutes per conversation. Otter is also a helpful tool to record and transcribe podcasts. The summary resembles a table of contents: clicking sections will take you to that spot in the recorded audio, making recordings easy to navigate. Click image to enlarge.Īdd comments to the transcript and share with your group. Otter automatically generates meeting transcripts and summaries, turning voices into text and capturing slides.
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