Based on our record, AssemblyAI should be more popular than Chatfuel. It has been mentiond 8 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
You can use a service like LinkDM or Chatfuel to auto DM anyone that comments on your posts, reels or stories, but you cannot auto DM anyone that follows you. Source: about 1 year ago
You can use an Instagram approved Inbox marketing solution like LinkDM or Chatfuel to automatically DM the shopping link to anyone that comments on the Post, Reel or Story. Source: over 1 year ago
A few months ago, I did a lot of research on this subject. I have tried many chatbots. In my opinion, Chatfuel is the best. Source: almost 3 years ago
The auto caption is from assemblyai.com, they do a pretty good job. As for manual, you can do `Add Layer` > `Text` from the short-form editor then trim each text layer. Its slow going though. Ideally we will figure out a better interface and build it. For now I recommend using the auto caption, then modifying it to your liking, if there is more than a few words it will probably be faster. Thanks for the kind words! Source: about 1 year ago
Assemblyai is a great tool for extracting transcripts from videos, I have used it for investor presentations from other sources. - Source: dev.to / almost 2 years ago
AssemblyAI is pioneering accurate and accessible speech recognition powered by cutting edge Deep Learning, Machine Learning, and AI research. Its Speech-to-Text API transcribes audio and video files and live audio streams with industry-best accuracy. In addition, the company offers Audio Intelligence APIs that secure higher ROI for users, including Sentiment Analysis, Topic Detection, Content Moderation, Auto... - Source: dev.to / over 2 years ago
Check out http://assemblyai.com/ - the API has pretty good Diarization results and is free for small volumes of data. Source: over 2 years ago
Hello r/python community. I spent a couple weeks analyzing some podcast data from Up First and The Daily over the last year, 8/21/2020 to 8/21/2021 and compared spikes in the frequency of negative news in the podcast to how the stock market performed over the last year. Specifically against the DJIA, the NASDAQ, and the price of Gold. I used Python Selenium to crawl ListenNotes to get links to the mp3 files,... Source: almost 3 years ago
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