tevr-asr-tool VS Typesense

Do some cool open source stuff. Since August 9th, I received about 50 job offers mentioning this repo: https://github.com/DeutscheKI/tevr-asr-tool Most of them were senior engineer or AI researcher, with a few CTO / co-founder offers sprinkled in. I'm not in the market and this was a bit unexpected to me, but those emails sounded like they would pay well. And most was remote for US companies.

Me, because I plan to extend to realtime processing: https://github.com/DeutscheKI/tevr-asr-tool

Also, all the performance critical stuff on my production servers is C++ with JNI or pybind wrappers.

The unique work that makes this speech recognition superior to other tools is in those 284 lines of code: https://github.com/DeutscheKI/tevr-asr-tool/blob/master/tevr...

That's a custom-designed beam search decoder implemented in C++ and based on the research for my TEVR paper. It increases performance by a relative 16% reduction in word error rate.

There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).

- Typesense (https://github.com/typesense/typesense)

- Algolia

- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)

Typesense - Open Source Alternative to Algolia

If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.

I work on Typesense [1] (historically considered an open source alternative to Algolia).

We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.

You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]

You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).

You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.

[1] https://github.com/typesense/typesense

[2] https://typesense.org/docs/0.25.0/api/vector-search.html

For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense

I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.

A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.

Try tigris | typesense for faster search

I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/